bluuebunny/crossref_metadata_2025 huggingface dataset:
Trends and Perspectives of mHealth in Obesity Control
Authors: Kim Sang-Dol
Published: December 2024

The proliferation of mobile health (mHealth) technologies has revolutionized healthcare delivery, particularly in obesity control. This descriptive study aimed to identify the evolving trends and perspectives of mHealth interventions targeting obesity control, leveraging insights from the ChatGPT language model accessed on 1 January 2024. Eighteen items and 32 questions were used to assess trends and perspectives in mHealth for obesity control, with 8 items and 16 questions dedicated to each aspect, respectively. Key trends identified include personalized interventions, integration of emerging technologies, remote monitoring and telemedicine, behavioral economics strategies, and enhanced user engagement. Perspectives highlight potential for equity, empowerment through self-management, privacy and security concerns, evidence-based practice, and interdisciplinary approaches. These findings shed light on mHealth’s potential in combating obesity, offering valuable insights for healthcare practitioners, researchers, and policymakers. They underscore the significance of leveraging technology to address the global burden of obesity and advocate for collaborative efforts to maximize mHealth solutions’ impact on promoting healthier lifestyles and reducing obesity-related complications.
Re-(De)fined Level of Detail for Urban Elements: Integrating Geometric and Attribute Data
Authors: Boswick Benjamin , Pankratz Zachary , Glowacki Matthew , Lu Yuhao
Published: December 2024

The level of detail (LOD) differentiates multi-scale representations of virtual 3D city models; however, the LOD tends to relay primarily the geometric details of buildings. When the LOD extends to other datasets, such as vegetation, transportation, terrain, water bodies, and city furniture, their LODs are not as clearly defined. Despite the general acceptance of this categorization, existing LOD formats also neglect non-geometric attributes. Integrating geometric and attribute data enables geometrically accurate and data-rich 3D models, ensuring that representations are as accurate as possible and that analyses contain as much information as possible. This paper proposes a family of LOD definitions considering both geometric and attribute data based on the geometric complexity and difficulty of obtaining, archiving, processing, and distributing the data. These definitions are intended to apply to all datasets by determining divisions in the LOD typically experienced across urban 3D model elements and their associated datasets, including buildings, vegetation, roads, relief, water bodies, and city furniture. Universally applicable definitions for datasets allow individuals to recreate studies or representations of 3D models to ensure the relevant data are present. These definitions also assist data providers in evaluating their data infrastructure and further strategizing and prioritizing updates or upgrades.
Intensification of Natural Disasters in the State of Pará and the Triggering Mechanisms Across the Eastern Amazon
Authors: de Souza Everaldo B. , Ferreira Douglas B. S. , Anjos Luciano J. S. , Cunha Alan C. , Silva João Athaydes , Coutinho Eliane C. , Sousa Adriano M. L. , Souza Paulo J. O. P. , Correa Waleria P. Monteiro , Dias Thaiane S. Silva , do Carmo Alexandre M. C. , Gutierrez Carlos B. B. , Sodré Giordani R. C. , Lima Aline M. M. , Rocha Edson J. P. , Moraes Bergson C. , Pezzi Luciano P. , Ambrizzi Tercio
Published: December 2024

Based on statistical analyses applied to official data from the Digital Atlas of Disasters in Brazil over the last 25 years, we evidenced a consistent intensification in the annual occurrence of natural disasters in the state of Pará, located in the eastern Brazilian Amazon. The quantitative comparison between the averages of the most intense period of disasters (2017 to 2023) and the earlier years (1999 to 2016) revealed a remarkable percentage increase of 473%. Approximately 81% of the state’s municipalities were affected, as indicated by disaster mapping. A clear seasonal pattern was observed, with Hydrological disasters (Inundations, Flash floods, and Heavy rainfall) peaking between February and May, while Climatological disasters (Droughts and Forest fires) were most frequent from August to October. The catastrophic impacts on people and the economy were documented, showing a significant rise in the number of homeless individuals and those directly affected, alongside considerable material damage and economic losses for both the public and private sectors. Furthermore, we conducted a comprehensive composite analysis on the tropical ocean–atmosphere dynamic structure that elucidated the various triggering mechanisms of disasters arising from Inundations, Droughts, and Forest fires (on seasonal scale), and Flash floods and Heavy rainfall (on sub-monthly scale) in Pará. The detailed characterization of disasters on a municipal scale is relevant in terms of the scientific contribution applied to the strategic decision-making, planning, and implementation of public policies aimed at early risk management (rather than post-disaster response), which is critical for safeguarding human well-being and strengthening the resilience of Amazonian communities vulnerable to climate change.
Investigating the Temporal and Spatial Characteristics of Lower Atmospheric Ducts in the Arctic via Long-Term Numerical Simulations
Authors: Wang Jinyue , Zhao Xiaofeng , Zou Jing , Yang Pinglv , Wang Bo , Yang Shuai , Qiu Zhijin , Li Zhiqian , Hu Tong , Song Miaomiao
Published: December 2024

In this study, a diagnostic model for lower atmospheric ducts was developed using the polar weather research and forecasting model. A five-year simulation was then conducted across the entire Arctic region to investigate the temporal and spatial characteristics of lower atmospheric ducts. The model demonstrated excellent performance in simulating modified atmospheric refractivity, with root mean square errors ranging from 0 M to 5 M. The five-year simulation results revealed that duct occurrence rates across the Arctic region were all below 1% and exhibited a negative relationship with latitude. Regarding the difference between surface ducts and elevated ducts, a higher frequency of surface ducts was detected in the Arctic region. The height and thickness of surface ducts were generally lower than those of elevated ducts, but the strength of surface ducts was slightly greater. Regionally, surface ducts mainly occurred in the land areas surrounding the Arctic Ocean, while more elevated ducts were found in the North Atlantic Sea area. Additionally, a negative correlation was observed between the polar vortex indices and the characteristics of ducts, particularly for surface ducts. The ducts in Greenland were notably influenced by polar vortex activity, whereas the ducts in other regions, such as the Norwegian Sea and Kara Sea, were less affected.
Can Cryptogonimids of the Same Genus Influence Each Other’s Level of Genetic Variation?
Authors: Tokarskaya Ekaterina S. , Tatonova Yulia V. , Amissah Haneef Ahmed , Shumenko Polina G. , Shchelkanov Mikhail Yu.
Published: December 2024

Trematodes of the genus Exorchis are parasites that are common in East and Southeast Asia. These parasites are known to infect fish, thus impacting aquaculture significantly. An introspection into the dynamics of infection of these parasites has revealed possible co-infection in shared hosts. But data on the dynamics of their shared host on their population structure and genetic variability is lacking. In this study, we investigate the intraspecific structure of the Exorchis species, Exorchis oviformis, and E. convictus, both of which coexist in the same definitive host. By using partial gene sequences of the mitochondrial cox1 gene (715 bp), including 30 newly obtained sequences from the southern part of the Russian Far East, we found a low level of genetic variation in both species, consistent with previous findings of other trematodes from the same region. We hypothesize that the observed low variability could be attributable to the process of host infection and transmission and abiotic factors influencing a recent decline in host variability and abundance. This is driving a strong selection pressure due to the limited number of parasites reaching the definitive host. This, among other factors, could possibly impact the long-term survival and adaptability of Exorchis and other trematodes at large in the region. However, we also believe that there may be a chance that these closely related species could exert an influence on each other’s genetic diversity, potentially limiting the variation within each species. To uncover the dynamics driving these observations, we propose the approach of expanding sampling, broader genetic marker analyses, and investigations of varied host populations that could elucidate the complexities of the Exorchis species genetic variability and evolutionary dynamics.
Antarctic Toothfish Dissostichus mawsoni in the South Orkney Islands: Using Otolith Chemistry to Test Current Hypotheses About Nursery Areas and Demographic Units
Authors: Carimán Paulina , Niklitschek Edwin J. , Garcés Cristóbal , Leisen Mathieu , Barra Fernando , Romero Rurik
Published: December 2024

We used otolith chemistry to test and complement current hypotheses regarding habitat use and connectivity between Dissostichus mawsoni sub-populations in Area 48 of the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR). Sagittal otoliths from 45 fish sampled near the South Orkney Islands were analysed. Their elemental (Li, Na, Mg, Cr, Mn, Sr, Sn, and Ba relative to Ca) and isotopic (δ18O and δ13C) signatures were examined in both the nuclear and marginal regions, representing juvenile and adult stages. Potential nursery habitats were geo-located by comparing observed and expected δ18O values. Chemical differences between the nuclear and marginal regions indicated ontogenetic migrations to deeper offshore habitats, suggesting a distinct habitat shift between 11 and 13 years of life. The data supported the existence of two nursery origins contributing to the study area’s population. However, the exact locations of these origins remain unclear and did not provide direct support for the hypotheses currently under consideration by the CCAMLR. Therefore, further assessment of the connectivity between nursery and adult habitats, as well as spawning site fidelity, is necessary before ruling out alternative hypotheses.
Investigation of ITGB3 Heterogeneity to Overcome Trastuzumab Resistance in HER2-Positive Breast Cancer
Authors: Boz Er Asiye Busra
Published: December 2024

HER2-positive breast cancer has an aggressive tumour progression among breast cancers characterized by the overexpression of HER2. Trastuzumab is an FDA-approved drug and has significantly improved outcomes for patients; however, drug resistance remains a major challenge. Tumour heterogeneity, describing genetic, epigenetic, and phenotypic differences within and between tumours, complicates tumour treatment and contributes to drug resistance. Understanding the mechanisms underlying Trastuzumab resistance, such as tumour heterogeneity, is crucial for developing new and effective therapeutic strategies. This study investigates the role of ITGB3 heterogeneity in Trastuzumab resistance, focusing on its impact on TGF-β signalling and migration marker response. It also evaluates the potential of combining Trastuzumab with the integrin β3 inhibitor cilengitide to overcome resistance associated with ITGB3 levels. Trastuzumab-resistant HER2-positive HCC1954 and SKBR3 breast cancer cell lines were generated and analysed for ITGB3 expression heterogeneity. The impact of ITGB3 on TGF-β-responsive genes (WWP1, CARM1, RASGRP1, THBS1, KCTD5, SGCA, EIF3S6, MCAM, FXR2, MTMR3, SOCS3, SLC2A4RG, MMP2, MMP9, and HSP47) and cell migration (Col4a1, fibronectin, ICAM1, Timp2, and vimentin) was analysed using luciferase reporter assays and real-time PCR. The effects of combined treatment with Trastuzumab and cilengitide were also evaluated via wound closure assay. ITGB3 expression varied significantly among resistant clones, correlating with increased expression of TGF-β-responsive genes and enhanced migration markers. Combined treatment with Trastuzumab and cilengitide significantly reduced TGF-β signalling and migration-related gene expression, particularly in high ITGB3-expressing cells. ITGB3 plays a critical role in Trastuzumab resistance through the modulation of TGF-β signalling, migration, and contributing to tumour heterogeneity. Targeting ITGβ3, alone or in combination with cilengitide, offers a promising strategy to resensitize resistant HER2-positive breast cancer cells to Trastuzumab. These findings provide valuable insights into the mechanisms of Trastuzumab resistance and suggest potential therapeutic avenues for improving patient outcomes.
Discovery and Characterization of Two Selective Inhibitors for a Mu-Class Glutathione S-Transferase of 25 kDa from Taenia solium Using Computational and Bioinformatics Tools
Authors: Sánchez-Juárez César , Flores-López Roberto , Sánchez-Pérez Lluvia de Carolina , García-Gutiérrez Ponciano , Jiménez Lucía , Landa Abraham , Zubillaga Rafael A.
Published: December 2024

Glutathione S-transferases (GSTs) are promising pharmacological targets for developing antiparasitic agents against helminths, as they play a key role in detoxifying cytotoxic xenobiotics and managing oxidative stress. Inhibiting GST activity can compromise parasite viability. This study reports the successful identification of two selective inhibitors for the mu-class glutathione S-transferase of 25 kDa (Ts25GST) from Taenia solium, named i11 and i15, using a computationally guided approach. The workflow involved modeling and refining the 3D structure from the sequence using the AlphaFold algorithm and all-atom molecular dynamics simulations with an explicit solvent. Representative structures from these simulations and a putative binding site with low conservation relative to human GSTs, identified via the SILCS methodology, were employed for virtual screening through ensemble docking against a commercial compound library. The two compounds were found to reduce the enzyme’s activity by 50–70% under assay conditions, while showing a reduction of only 30–35% for human mu-class GSTM1, demonstrating selectivity for Ts25GST. Notable, i11 displayed competitive inhibition with CDNB, while i15 exhibited a non-competitive inhibition type.
The Mediating Role of Psychological Empowerment on the Relationship Between Digital Transformation, Innovative Work Behavior, and Organizational Financial Performance
Authors: Muneer Saqib , Singh Ajay , Choudhary Mazhar Hussain , Alshammari Awwad Saad
Published: December 2024

With the use of digital technologies in today’s innovation era, the financial sector has transformed how they facilitate customer business and generate a high level of revenue. This study aims to explore the relationship between innovative work behavior (IWB), digital transformation (DT), and organizational financial performance (OFP) to analyze the mediating role of workers’ psychological empowerment (PE) between independent and dependent variables. Further, we examined the moderating role of smart technologies (ST) between PE and OFP. This study collected data from Saudi banking sector employees using a well-structured questionnaire adopted from previous literature. Next, Smart-PLS was used to analyze the data using the structural equation modeling-partial least squares (SEM-PLS) approach. The results reveal that IW positively relates to OFP, with PE mediating this relationship. Furthermore, DT positively affects OFP. ST acts as a positive moderator that enhances workers’ PE and OFP. Meanwhile, PE, as a mediator, positively relates DT and IWB to OFP. Overall, this study makes valuable theoretical, empirical, and practical contributions, which can benefit bank management, policymakers, and future academic research.
Ethnic Architectural Heritage Identification Using Low-Altitude UAV Remote Sensing and Improved Deep Learning Algorithms
Authors: Luo Ting , Sun Xiaoqiong , Zhao Weiquan , Li Wei , Yin Linjiang , Xie Dongdong
Published: December 2024

Ethnic minority architecture is a vital carrier of the cultural heritage of ethnic minorities in China, and its quick and accurate extraction from remote sensing images is highly important for promoting the application of remote sensing information in urban management and architectural heritage protection. Taking Buyi architecture in China as an example, this paper proposes a minority architectural heritage identification method that combines low-altitude unmanned aerial vehicle (UAV) remote sensing technology and an improved deep learning algorithm. First, UAV images are used as the data source to provide high-resolution images for research on ethnic architecture recognition and to solve the problems associated with the high costs, time consumption, and destructiveness of traditional methods for ethnic architecture recognition. Second, to address the lack of edge pixel features in the sample images and reduce repeated labeling of the same sample, the ethnic architecture in entire remote sensing images is labeled on the Arcgis platform, and the sliding window method is used to cut the image data and the corresponding label file with a 10% overlap rate. Finally, an attention mechanism SE module is introduced to improve the DeepLabV3+ network model structure and achieve superior ethnic building recognition results. The experimental data fully show that the model’s accuracy reaches as high as 0.9831, with an excellent recall rate of 0.9743. Moreover, the F1 score is stable at a high level of 0.9787, which highlights the excellent performance of the model in terms of comprehensive evaluation indicators. Additionally, the intersection/union ratio (IoU) of the model is 0.9582, which further verifies its high precision in pixel-level recognition tasks. According to an in-depth comparative analysis, the innovative method proposed in this paper solves the problem of insufficient feature extraction of sample edge pixels and substantially reduces interference from complex environmental factors such as roads, building shadows, and vegetation with the recognition results for ethnic architecture. This breakthrough greatly improves the accuracy and robustness of the identification of architecture in low-altitude remote sensing images and provides strong technical support for the protection and intelligent analysis of architectural heritage.
An Analysis of Factors Contributing to Cost Overruns in the Global Construction Industry
Authors: Abdelalim Ahmed Mohammed , Salem Maram , Salem Mohamed , Al-Adwani Manal , Tantawy Mohamed
Published: December 2024

The construction industry builds infrastructure and strengthens the global economy, but it struggles with cost overruns. This systematic study used scientometrics and Social Network Analysis to examine the multifaceted factors causing construction project cost escalations. After reviewing 405 scholarly works, the research mapped and analyzed 66 interconnected cost overrun factors in 69 high-impact studies between 2000 and 2024. To uncover the patterns, the study used two main research methods. First, this study applied a scientometric analysis that reviewed trends and gaps from the previous studies. Second, this study used Social Network Analysis (SNA) to examine how different factors were connected and which factors had the strongest influence on cost overruns. The methodology comprised a systematic literature search, document selection, scientometric analysis, factor standardization, and an SNA application. Seven critical drivers with high network centrality were identified: planning and scheduling issues, project estimation inaccuracies, design inefficiencies, negative weather conditions, scope definition challenges, contractual ambiguities, and unforeseeable site conditions. By applying the SNA degree centrality (DC), the analysis quantified the significance of each factor within the network. With the use of this dual analysis, a novel mapping of the main causes of cost overruns was produced, leading to the discovery of seven core factors that significantly affected project outcomes, including planning and scheduling issues, project estimation problems, and design inefficiencies. The findings advance the knowledge of the dynamics of cost overruns and offer practical insights for enhancing cost management practices in the construction industry.
Seismic Resilience Evaluation of High-Rise Frame-Core Tube Structure Considering Structural Network Performance Loss and Repair Path
Authors: Lu Jianfeng , Li Zuohua , Teng Jun
Published: December 2024

Structural seismic resilience is influenced by both the structural performance loss (loss) and the repair path (path). Some studies ensure the reality of path but lack accuracy of loss. Others ensure the accuracy of loss but lack the reality of path. Therefore, this paper proposes a new resilience evaluation method for frame-core tube structure that considers both loss and path. Firstly, the complex network method is used to establish structural network performance and its loss index. Next, the repair path is determined by updating the network performance after component repairs. Then, a resilience index that considers both network performance loss and repair path is proposed. Finally, the resilience of the case structures is evaluated and compared with methods that do not reasonably consider loss or path. The results indicate that the proposed method can comprehensively consider the impact of loss and path on resilience. Loss has a greater impact on resilience when the structure is less than slight loss or is in the late stage of moderate loss. Path has a greater impact on resilience when the structure is slight loss or is in the early stage of moderate loss. When only considering loss, the fixed linear path underestimates the resilience of a convex-shaped path and overestimates the resilience of a concave-shaped path. When only considering path, underestimating or overestimating loss can lead to a higher or lower resilience. Particularly when the structure is in the late stage of moderate loss, resilience dropped from 89.16% to 42.04% due to overestimation of loss.
Effect of Dynamic Window Opening Behaviors on Indoor Thermal Environment and Energy Consumption in Residential Buildings of Different Chinese Thermal Climate Zones
Authors: Guo Fangpeng , Chen Zhenqian , Wang Jun
Published: December 2024

Residential occupant window opening behavior has a significant impact on building design optimization, energy consumption diagnosis, performance evaluation and energy simulation. However, there has not been much research quantifying the evaluation of window opening behaviors’ influence with respect to residential thermal comfort and HVAC energy for different thermal climate zones in China. Therefore, this paper compared the impacts of six window opening models on HVAC energy consumption and thermal comfort in residential buildings across five thermal climate zones in China through a series of simulation tests using a building performance simulation software. The results indicated that in terms of thermal comfort, the optimal window opening model is WOM-3 (the window opening model based on outdoor air temperature) for Shenyang, Beijing, Wuhan, and Guangzhou, with thermal comfort hours of 2076, 2065, 2244, and 3491, and WOM-6 (the window opening model based on occupant window opening schedules) was optimal for Kunming with thermal comfort hours of 3292. With respect to HVAC energy consumption, the window opening models WOM-3, WOM-4 (the window opening model based on 15 ≤ Tout ≤ Tin ≤ 28), and WOM-6 (the window opening model based on outdoor air temperature Coupled 15 ≤ Tout ≤ 28 and the occupant window opening schedules) were found to be optimal for Shenyang, Beijing, Wuhan, Guangzhou, and Kunming. When taking thermal comfort and HVAC energy into consideration, the outdoor air temperature-based WOM-3 is the ideal window opening model. Moreover, the optimal window opening model for each month has been elucidated.
Applying Improved Performance-Based Instructions to Investigate Seismic Performance of a Code-Conforming Steel Trussed-Tube Building
Authors: Zhao Pei-Pei , Wang Zhen-Yu , Babaei Masoud , Asemi Kamran
Published: December 2024

Despite the many advantages of tube systems with braces, known as trussed tubes, no specific seismic design criteria exist in the current regulations to design them, and practitioners utilize common methods used for common building structures to deal with designing such systems. The aim of this study is to investigate the performance of a 31-story steel trussed-tube building designed according to the customary design provisions. To evaluate the performance of the code-conforming designed structure, a three-dimensional nonlinear static (pushover) analysis is employed, and the acceptance criteria corresponding to different performance levels are examined. The obtained performance-based results are then compared with the design based on the customary guidelines, and the shortcomings of common design regulations in the design of trussed-tube buildings are highlighted. By observing the state of the plastic hinges, as well as force-controlled joints at two distinct earthquake hazard levels, it is found that the structure under study, which was loaded, analyzed, and designed exactly in compliance with the requirements of the regulations and standards, does not satisfy the performance criteria. In a typical nonlinear brace hinge, for instance, the results indicate that the LS acceptance criterion has been exceeded by approximately 30 percent at the BSE-1 hazard level. Also, the drifts surpass the 1% limit at specific levels, with the maximum drift reaching approximately 1.4%. As a result, the design of trussed-tube systems based on common codes and regulations can lead to an unsafe design that lacks the expected performance intended in their service life.
Predictive Analytics in Construction: Multi-Output Machine Learning Models for Abrasion Resistance
Authors: Ahmed Shaheen Mohammed Saleh , Güneyli Hakan , Karahan Süleyman
Published: December 2024

This study aims to accurately predict abrasion resistance, measured through the Los Angeles (LA) abrasion test, and modulus of elasticity, assessed using the Micro-Deval Abrasion (MDA) test, to support structural integrity and efficient material use in construction projects. We applied multi-output machine learning models—specifically Linear Regression (LR), Huber, RANSAC, and Support Vector Regression (SVR)—to predict LA and MDA values based on primary input parameters, including Uniaxial Compression Strength (UCS), Point Load Index (PLI), Schmidt Hammer Rebound (Sh_h), and Ultrasonic Pulse Velocity (UPV). The experimental work involved assessing model performance using metrics such as Mean Absolute Error (MAE), R-squared (R2), and Mean Squared Error (MSE). Linear Regression demonstrated superior predictive accuracy, achieving 94% for R2 with an MAE of 0.21 and MSE of 0.09 for LA predictions and 92% for R2 with an MAE of 0.24 and MSE of 0.11 for MDA predictions. These results underscore the potential of machine learning techniques in accurately predicting critical material properties, offering engineers reliable tools for optimizing material selection and structural design. This research contributes to the advancement of construction practices, promoting the development of durable and efficient infrastructure.
Performance Evaluation of Machine Learning Models for Predicting Energy Consumption and Occupant Dissatisfaction in Buildings
Authors: Hosamo Haidar , Mazzetto Silvia
Published: December 2024

This study evaluates the performance of 15 machine learning models for predicting energy consumption (30–100 kWh/m2·year) and occupant dissatisfaction (Percentage of Dissatisfied, PPD: 6–90%), key metrics for optimizing building performance. Ten evaluation metrics, including Mean Absolute Error (MAE, average prediction error), Root Mean Squared Error (RMSE, penalizing large errors), and the coefficient of determination (R2, variance explained by the model), are used. XGBoost achieves the highest accuracy, with an energy MAE of 1.55 kWh/m2·year and a PPD MAE of 3.14%, alongside R2 values of 0.99 and 0.97, respectively. While these metrics highlight XGBoost’s superiority, its margin of improvement over LightGBM (energy MAE: 2.35 kWh/m2·year, PPD MAE: 3.89%) is context-dependent, suggesting its application in high-precision scenarios. ANN excelled at PPD predictions, achieving the lowest MAE (1.55%) and Mean Absolute Percentage Error (MAPE: 4.97%), demonstrating its ability to model complex nonlinear relationships. This nonlinear modeling advantage contrasts with LightGBM’s balance of speed and accuracy, making it suitable for computationally constrained tasks. In contrast, traditional models like linear regression and KNN exhibit high errors (e.g., energy MAE: 17.56 kWh/m2·year, PPD MAE: 17.89%), underscoring their limitations with respect to capturing the complexities of building performance datasets. The results indicate that advanced methods like XGBoost and ANN are particularly effective owing to their ability to model intricate relationships and manage high-dimensional data. Future research should validate these findings with diverse real-world datasets, including those representing varying building types and climates. Hybrid models combining the interpretability of linear methods with the precision of ensemble or neural models should be explored. Additionally, integrating these machine learning techniques with digital twin platforms could address real-time optimization challenges, including dynamic occupant behavior and time-dependent energy consumption.
The RAGE Inhibitor TTP488 (Azeliragon) Demonstrates Anti-Tumor Activity and Enhances the Efficacy of Radiation Therapy in Pancreatic Cancer Cell Lines
Authors: Alka Kumari , Oyeniyi Jacob F. , Mohammad Ghulam , Zhao Yi , Marcus Stephen , Chinnaiyan Prakash
Published: December 2024

Pancreatic cancer is the third leading cause of cancer-related mortality in the United States, with rising incidence and mortality. The receptor for advanced glycation end products (RAGE) and its ligands significantly contribute to pancreatic cancer progression by enhancing cell proliferation, fostering treatment resistance, and promoting a pro-tumor microenvironment via activation of the nuclear factor-kappa B (NF-κB) signaling pathways. This study validated pathway activation in human pancreatic cancer and evaluated the therapeutic efficacy of TTP488 (Azeliragon), a small-molecule RAGE inhibitor, alone and in combination with radiation therapy (RT) in preclinical models of pancreatic cancer. Human (Panc1) and murine (Pan02) pancreatic cancer cell lines exhibited elevated levels of RAGE and its ligands compared to normal pancreatic tissue. In vitro, Azeliragon inhibited RAGE-mediated NF-κB activation and ligand-mediated cell proliferation in pancreatic cancer cell lines. Target engagement of Azeliragon was confirmed in vivo, as determined by decreased NF-κB activation. Azeliragon demonstrated significant growth delay in mouse models of pancreatic cancer and additive effects when combined with RT. Additionally, Azeliragon modulated the immune suppressive tumor microenvironment in pancreatic cancer by reducing immunosuppressive cells, including M2 macrophages, regulatory T cells, and myeloid-derived suppressor cells, while enhancing CD8+ T cell infiltration. These findings suggest that Azeliragon, by inhibiting RAGE-mediated signaling and modulating immune response, may serve as an effective anti-cancer agent in pancreatic cancer.
Prospects for Narrow Band Imaging Magnification Endoscopy in Oral Lesions: Recommendations from Oral and Maxillofacial Surgeons and a Gastroenterologist
Authors: Chiba Toshimi , Ota Airi , Hirano Taifu , Kawai Tadashi , Ogawa Atsushi , Yamada Hiroyuki
Published: December 2024

Narrow band imaging (NBI) magnification endoscopy for the diagnosis of early-stage oral cavity-related cancer and precancerous lesions can recognize oral lesions as brownish areas, and can observe intraepithelial papillary capillary loops (IPCLs) in the mucosa and submucosa to make a qualitative diagnosis of the lesion and highlight the mucosal surface microstructure to facilitate appropriate diagnosis and early treatment. IPCLs are classified from Type 0 to IV: Type 0 is normal mucosa or no blood vessels observed, e.g., in keratinization; Type I is mainly normal mucosa; Type II is mainly inflammatory sites or non-malignant lesions; Type III is mainly precancerous or suspected malignant lesions; and Type IV is cancerous or malignant lesions. NBI magnification endoscopy is a useful noninvasive method for identifying the malignant transformation of oral potentially malignant disorders (OPMDs). Oral lesions classified as IPCL Type II or higher are atypical epithelial or oral squamous cell carcinoma (OSCC); oral biopsy is recommended for early and accurate diagnosis, and is an indicator of the appropriate biopsy site in the follow-up for OPMDs. In the future, the accuracy of NBI magnification endoscopy for malignant transformation of OPMDs and OSCC will be further confirmed.
Beyond the Burn: Leukemia Threats Following Radioactive Iodine Ablation Therapy for Thyroid Cancer
Authors: Hussein Mohammad H. , Toraih Eman , Jishu Jessan A. , Lavorgna Tessa , Abdelmaksoud Ahmed , Craig Ryan , Kandil Emad
Published: December 2024

Background: Radioactive iodine (RAI) ablation therapy is a common minimally invasive treatment for patients diagnosed with differentiated thyroid cancer (DTC). Although previous studies have identified a link between RAI and the mortality from secondary solid cancers, the connection between RAI and leukemia remains under-researched. This study investigated the differential risk of leukemia and its subtypes in DTC patients following RAI treatment. Methods: DTC patients from the Surveillance, Epidemiology, and End Results (SEER) Registry 17 (2000–2019) were analyzed. The standard incidence ratio (SIR) and excess risk (ER) compared to the reference population were calculated. Results: Out of 196,569 DTC patients, 1381 patients developed various types of hematological malignancies. Leukemia was diagnosed in 508 of these patients, and it had the highest risk among the malignancies studied, with an SIR of 1.74 (95%CI: 1.59–1.9). The RAI group had an SIR of 2.12 (95%CI: 1.87–2.39), while the non-RAI group had an SIR was 1.45 (95%CI: 1.37–1.52) (p < 0.001). Those diagnosed before the age of 55 years had a conspicuously elevated risk (SIR 2.74) compared to those diagnosed at 55 years or older (SIR 1.53). American Indian/Alaska Native survivors manifested a pronounced leukemia risk with an SIR of 7.63 (95%CI: 2.46–17.8). Conclusions: RAI treatment increased the risk of developing leukemia when serving as adjuvant therapy in surgical patients (SIR 2.12). There exists a significant association between RAI treatment in DTC patients and the incidence of leukemia. This susceptibility seems to be modulated by factors including time since diagnosis, age, gender, and racial background.
miRNAs Dysregulated in Human Papillomavirus-Associated Benign Prostatic Lesions and Prostate Cancer
Authors: Salgado-Hernández Sandra Viridiana , Martínez-Retamoza Lucero , Ocadiz-Delgado Rodolfo , Pérez-Mora Salvador , Cedeño-Arboleda Gladys Edith , Gómez-García María del Consuelo , Gariglio Patricio , Pérez-Ishiwara David Guillermo
Published: December 2024

Prostate pathologies, including chronic prostatitis, benign prostatic hyperplasia (BPH), and prostate cancer (PCa), are strongly associated with chronic inflammation, which is a key risk factor and hallmark of these diseases [...]
Hydrogen Production from Ethanol Steam Reforming by Stable LaNixCu1−xO3−λ Perovskite-Type Catalysts
Authors: Ruan Chenjie , Dou Binlin , Chen Na , Zhang Hua
Published: December 2024

Hydrogen production from ethanol steam reforming (ESR) was performed using the synthesized LaNixCu1−xO3−λ perovskite-type catalysts in a continuous two-stage fixed-bed reactor from 450 to 700 °C under atmospheric pressure. The elemental analysis (EA), XRD, SEM, BET, and TGA-DTG technologies were used to characterize the structures and properties of the synthesized catalysts. The thermodynamic equilibrium model, based on the minimization of Gibbs free energy using a non-stoichiometric methodology, was carried out and compared with experimental data. The results demonstrated that the catalytic activity of the perovskite-type catalysts for ESR can be improved after modification with a certain amount of copper (about 0.67 mmol/g) and decreased further with an increase in copper content (about 3.41 mmol/g). The most active catalyst was found to be LaNi0.9Cu0.1O3−λ, with an ethanol conversion value of 96.0% and hydrogen selectivity of 71.3%. The perovskite-type catalysts with an appropriate amount of Cu promoter improved coking resistance and presented excellent stability with no loss of activity over 101 h at 700 °C. Based on the power-law kinetic model with the first reaction order, the activation energy and the frequency factor for ethanol steam reforming by perovskite-type catalysts were calculated. Our studies indicated the enhanced effects of Ni and Cu on the small Ni-Cu bimetallic particles in the water gas shift (WGS) reaction, which could also contribute to the activity and stability of the LaNixCu1−xO3−λ perovskite-type catalysts in hydrogen production.
Hair Regeneration Methods Using Cells Derived from Human Hair Follicles and Challenges to Overcome
Authors: Hamida Ons Ben , Kim Moon Kyu , Sung Young Kwan , Kim Min Kyu , Kwack Mi Hee
Published: December 2024

The hair follicle is a complex of mesenchymal and epithelial cells acquiring different properties and characteristics responsible for fulfilling its inductive and regenerative role. The epidermal and dermal crosstalk induces morphogenesis and maintains hair follicle cycling properties. The hair follicle is enriched with pluripotent stem cells, where dermal papilla (DP) cells and dermal sheath (DS) cells constitute the dermal compartment and the epithelial stem cells existing in the bulge region exert their regenerative role by mediating the epithelial–mesenchymal interaction (EMI). Many studies have developed and focused on various methods to optimize the EMI through in vivo and in vitro approaches for hair regeneration. The culturing of human hair mesenchymal cells resulted in the loss of trichogenicity and inductive properties of DP cells, limiting their potential application in de novo hair follicle generation in vivo. Epithelial stem cells derived from human hair follicles are challenging to isolate and culture, making it difficult to obtain enough cells for hair regeneration purposes. Mesenchymal stem cells and epithelial stem cells derived from human hair follicles lose their ability to form hair follicles during culture, limiting the study of hair follicle formation in vivo. Therefore, many attempts and methods have been developed to overcome these limitations. Here, we review the possible and necessary cell methods and techniques used for human hair follicle regeneration and the restoration of hair follicle cell inductivity in culture.
Mechanistic Insights into Sugar Racemization and Oxidative Degradation via Fenton and Alkaline Peroxide Systems
Authors: Köntös Zoltán , Németh Áron
Published: December 2024

This study explores the oxidation and racemization of selected C5 and C6 sugars using hydrogen peroxide (H2O2) in alkaline and Fenton reaction conditions. The sugars studied include D-Glucose, D-Fructose, D-Mannose, D-Xylose, D-Lactose, D-Arabinose, D-Cellobiose, Sucrose, and D-Galactose. Oxidation reactions were conducted using both Fenton’s reagent and NaOH/H2O2 to examine product formation, yield distribution, and stereochemical transformations. Under alkaline conditions, sugars primarily oxidized to yield sodium formate and hydrogen, with the minimal formation of intermediate sugar acids. Excess alkaline conditions further promoted the rapid degradation of sugars to sodium formate and hydrogen as primary products, indicating the strong influence of reaction conditions on oxidation pathways. A significant observation was that both alkaline and Fenton oxidation led to racemization, converting optically pure sugars into a racemic mixture of D- and L-enantiomers, thus producing products with zero optical rotation. The generation of L-enantiomers, metabolically inactive in biological systems, has implications for energy yield and biochemical efficiency.
Transmembrane Amino Acid Transporters in Shaping the Metabolic Profile of Breast Cancer Cell Lines: The Focus on Molecular Biological Subtype
Authors: Dyachenko Elena I. , Bel’skaya Lyudmila V.
Published: December 2024

Amino acid metabolism in breast cancer cells is unique for each molecular biological subtype of breast cancer. In this review, the features of breast cancer cell metabolism are considered in terms of changes in the amino acid composition due to the activity of transmembrane amino acid transporters. In addition to the main signaling pathway PI3K/Akt/mTOR, the activity of the oncogene c-Myc, HIF, p53, GATA2, NF-kB and MAT2A have a direct effect on the amino acid metabolism of cancer cells, their growth and proliferation, as well as the maintenance of homeostatic equilibrium. A distinctive feature of luminal subtypes of breast cancer from TNBC is the ability to perform gluconeogenesis. Breast cancers with a positive expression of the HER2 receptor, in contrast to TNBC and luminal A subtype, have a distinctive active synthesis and consumption of fatty acids. It is interesting to note that amino acid transporters exhibit their activity depending on the pH level inside the cell. In the most aggressive forms of breast cancer or with the gradual progression of the disease, pH will also change, which will directly affect the metabolism of amino acids. Using the cell lines presented in this review, we can trace the characteristic features inherent in each of the molecular biological subtypes of breast cancer and develop the most optimal therapeutic targets.
Effect of Sintering Temperature on Tensile Properties of Ti-6Al-4V Alloy Manufactured Through Metal Injection Molding
Authors: Mai Zhengyang , Wang Haiying , Su Yongjun , Zhang Changjiang , Miao Yigao , Zhou Chuancang , Xu Lili
Published: December 2024

Titanium and titanium alloys exhibit low density, high strength and excellent corrosion resistance, and have become workhorses in modern aerospace and chemical processing industries. Recently, Ti-6Al-4V alloy has been manufactured through metal injection molding (MIM). MIM is widely utilized in various manufacturing industries due to the near-net-forming process, especially in the preparation of difficult-to-deform high-temperature alloys. Sintering temperature is vital to ensuring good tensile mechanical properties. In this work, Ti-6Al-4V alloy was sintered under various sintering temperatures, from 1150 to 1250 °C. The effect of sintering temperature on the mechanical properties was evaluated. The tensile test results exhibited that a yield strength of 896.35 MPa, an ultimate tensile strength of 980.83 MPa and plastic elongation of 9.61% were produced at 1150 °C for 4 h; a yield strength of 877.23 MPa, an ultimate tensile strength of 981.92 MPa and plastic elongation of 7.74% were produced at 1200 °C for 4 h; and a yield strength of 923.33 MPa, an ultimate tensile strength of 1002.24 MPa and plastic elongation of 6.57% were produced at 1250 °C for 4 h.
Characterization and Optimization of Boride Coatings on AISI 1137 Steel: Enhancing Surface Properties and Wear Resistance
Authors: Genç Asım , Urtekin Levent , Danışmaz Merdin
Published: December 2024

This study investigates the optimization of boron coating parameters for medium-carbon steels, specifically AISI 1137, and their subsequent effects on mechanical properties, which are crucial for industrial applications. Despite extensive research on boronizing processes, an understanding of the optimal conditions that enhance wear resistance and hardness while maintaining structural integrity is still lacking. To address this gap, we systematically examined the impact of boronizing temperatures (850 °C and 950 °C) and durations (2, 4, and 8 h) on the structural and mechanical properties of AISI 1137 steel. Our findings indicate the need for improved surface properties in medium-carbon steels used in demanding environments, such as automotive and machinery components. The boronizing process was carried out using Ekabor 1 powder, with characterization performed through optical microscopy, pin-on-disk wear tests, and Vickers hardness analysis. Results showed that the thickness of the boronized layer ranged from 50.6 μm to 64.8 μm, with wear resistance increasing by 1.8 to 3.9 times at 950 °C compared to at 850 °C. The measured hardness of the boronized surface layers varied between 1963.7 HV and 219.3 HV, decreasing from the boronized layer toward the base material. The optimal parameters for wear resistance and hardness were found to be a temperature of 950 °C and a duration of 8 h, facilitating the formation of FeB and Fe2B phases, which significantly enhanced the steel’s mechanical properties. This research provides valuable insights into the boronizing process and establishes a foundation for the optimizing of surface treatments to extend the lifespan and performance of medium-carbon steels in industrial use.
Investigation of the Interface Diffusion Layer’s Impact on the Thermal Cycle Life of PS-PVD Thermal Barrier Coatings
Authors: He Qing , Li Xinhui , Zhang Yusheng , Li Jianchao , You Xiaoming
Published: December 2024

The behaviour of the interdiffusion layer between the ceramic layer and the metal bonding layer in thermal barrier coatings, resulting from high-energy beam coating deposition, is a critical factor influencing the thermal cycle life of these coatings. Given that the interdiffusion layer at the interface of plasma spray-physical vapour deposition (PS-PVD) coatings has been relatively underexplored and its influencing mechanisms remain unclear, this study investigates how different pre-oxidation layer states affect the thermal cycle life of PS-PVD coatings. Under conditions conducive to effective pre-oxidation film formation and minimal interdiffusion between NiCrAlYSi and 8YSZ, we observed an increase in thermal cycle life from 1000 h at 1100 °C to 2150 h. The application of high-heat flux jets, along with coupling factors related to preheating and pre-oxidation processes, can modulate interdiffusion at the interface. A thinner interdiffusion layer not only reduces oxidation rates but also enhances the longevity of the coating’s thermal cycle. Ultimately, cracks may develop within the composite oxide film, leading to coating failure. The Al-rich component present in both the interdiffusion composite oxide diffusion layer and initially deposited gas phase 8YSZ contributes to a reduction in TGO growth rate, as well as interface stress levels. In scenarios involving high-heat flux jet preheating coupled with coating deposition processes, the oxygen ion concentration emerges as a pivotal factor regulating interdiffusion dynamics. This research holds significant implications for elucidating the formation mechanisms underlying interdiffusion layers while simultaneously enhancing PS-PVD coating lifespans.