bluuebunny/crossref_metadata_2025 huggingface dataset:
PEP-1–PIN1 Promotes Hippocampal Neuronal Cell Survival by Inhibiting Cellular ROS and MAPK Phosphorylation
Authors: Park Jung Hwan , Shin Min Jea , Youn Gi Soo , Yeo Hyeon Ji , Yeo Eun Ji , Kwon Hyun Jung , Lee Lee Re , Kim Na Yeon , Kwon Su Yeon , Kim Su Min , Cho Yong-Jun , Lee Sung Ho , Jung Hyo Young , Kim Dae Won , Eum Won Sik , Choi Soo Young
Published: October 2024

Background: The peptidyl-prolyl isomerase (PIN1) plays a vital role in cellular processes, including intracellular signaling and apoptosis. While oxidative stress is considered one of the primary mechanisms of pathogenesis in brain ischemic injury, the precise function of PIN1 in this disease remains to be elucidated. Objective: We constructed a cell-permeable PEP-1–PIN1 fusion protein and investigated PIN1’s function in HT-22 hippocampal cells as well as in a brain ischemic injury gerbil model. Methods: Transduction of PEP-1–PIN1 into HT-22 cells and signaling pathways were determined by Western blot analysis. Intracellular reactive oxygen species (ROS) production and DNA damage was confirmed by DCF-DA and TUNEL staining. Cell viability was determined by MTT assay. Protective effects of PEP-1-PIN1 against ischemic injury were examined using immunohistochemistry. Results: PEP-1–PIN1, when transduced into HT-22 hippocampal cells, inhibited cell death in H2O2-treated cells and markedly reduced DNA fragmentation and ROS production. This fusion protein also reduced phosphorylation of mitogen-activated protein kinase (MAPK) and modulated expression levels of apoptosis-signaling proteins in HT-22 cells. Furthermore, PEP-1–PIN1 was distributed in gerbil hippocampus neuronal cells after passing through the blood–brain barrier (BBB) and significantly protected against neuronal cell death and also decreased activation of microglia and astrocytes in an ischemic injury gerbil model. Conclusions: These results indicate that PEP-1–PIN1 can inhibit ischemic brain injury by reducing cellular ROS levels and regulating MAPK and apoptosis-signaling pathways, suggesting that PIN1 plays a protective role in H2O2-treated HT-22 cells and ischemic injury gerbil model.
Enhancing Brain Tumor Diagnosis with L-Net: A Novel Deep Learning Approach for MRI Image Segmentation and Classification
Authors: Dénes-Fazakas Lehel , Kovács Levente , Eigner György , Szilágyi László
Published: October 2024

Background: Brain tumors are highly complex, making their detection and classification a significant challenge in modern medical diagnostics. The accurate segmentation and classification of brain tumors from MRI images are crucial for effective treatment planning. This study aims to develop an advanced neural network architecture that addresses these challenges. Methods: We propose L-net, a novel architecture combining U-net for tumor boundary segmentation and a convolutional neural network (CNN) for tumor classification. These two units are coupled such a way that the CNN classifies the MRI images based on the features extracted by the U-net while segmenting the tumor, instead of relying on the original input images. The model is trained on a dataset of 3064 high-resolution MRI images, encompassing gliomas, meningiomas, and pituitary tumors, ensuring robust performance across different tumor types. Results: L-net achieved a classification accuracy of up to 99.6%, surpassing existing models in both segmentation and classification tasks. The model demonstrated effectiveness even with lower image resolutions, making it suitable for diverse clinical settings. Conclusions: The proposed L-net model provides an accurate and unified approach to brain tumor segmentation and classification. Its enhanced performance contributes to more reliable and precise diagnosis, supporting early detection and treatment in clinical applications.
Effects of Far-Infrared Rays Emitted from Loess Bio-Balls on Lymphatic Circulation and Reduction of Inflammatory Fluids
Authors: Shin Yong Il , Kim Min Seok , Yang Yeong Ae , Jeon Gye Rok , Kim Jae Ho , Choi Yeon Jin , Choi Woo Cheol , Kim Jae Hyung
Published: October 2024

Background: FIR therapy is used in various medical settings to treat diseases associated with inflammation and edema. Unlike conventional FIR lamp therapy, this study investigated how body fluids change depending on the intensity and duration of FIR irradiation to the whole body. Method: Subjects in group A (n = 27) were exposed to FIR emitted from a loess bio-ball mat set at 40 °C for 30 min, and subjects in group B (n = 27) were exposed to FIR emitted from a loess bio-ball mat set at 30 °C for 7 h during sleep. Changes in bioimpedance parameters and fluid-related values were measured using a body fluid analyzer before and after exposure to FIR. Results: Changes in bioimpedance parameters associated with inflammatory fluids were quantitatively confirmed. In group A, there was a minimal change in fluid-related measurements. However, significant changes in bioimpedance parameters associated with inflammatory fluids were observed in group B exposure to FIR for 7 h during sleep. Conclusions: FIR emitted from loess bio-balls activates biological tissues and lymphatic circulation, gradually reducing the levels of inflammatory fluids over time.
Fluctuations in Medium Viscosity May Affect the Stability of the CAG Tract in the ATXN2 Gene
Authors: Dorohova Anna , Lyasota Oksana , Dzhimak Stepan , Svidlov Alexandr , Leontyeva Olga , Drobotenko Mikhail
Published: October 2024

Background: Trinucleotide repeats are the cause of many neurodegenerative diseases that are currently incurable. In this regard, the question of the causes of occurrence and methods of prevention or treatment of diseases caused by the expansion of repeats in the CAG tract of the ATXN2 gene remains relevant. Previously, it was shown that the frequency of occurrence of additional OS (open states) zones increases with increasing length of the CAG tract, and the value inverse to the frequency correlates with the age of disease onset. Methods: In this work, the influence of the viscosity of the medium and the external torque on the stability of the CAG tract in the ATXN2 gene was studied using mathematical modeling methods. Results: It has been established that the probability of the appearance of additional OS zones of significant size increases with an increase in the CAG of the tract (k > 40 CAG repeats) for all viscosity values, however, at k ≤ 40, the change in viscosity does not significantly affect the probability of additional OS zones in the tract. Conclusions: It was found that under normal conditions (absence of pathology), viscosity does not have a reliable effect on the stability of the DNA molecule, but when pathology appears, an increase in viscosity contributes to an increase in DNA stability, and, accordingly, a decrease has a negative effect on the stabilization of the DNA molecule. In the zone of close to incomplete penetrance of the disease, viscosity does not have a reliable effect on the stability of the CAG tract.
Hepatic Bone Morphogenetic Protein and Activin Membrane-Bound Inhibitor Levels Decline in Hepatitis C but Are Not Associated with Progression of Hepatocellular Carcinoma
Authors: Weber Florian , Utpatel Kirsten , Evert Katja , Weiss Thomas S. , Buechler Christa
Published: October 2024

Background/Objectives: Bone morphogenetic protein and activin membrane-bound inhibitor (BAMBI) is an antagonist of transforming growth factor (TGF)-β type 1 signaling. BAMBI functions as an anti-fibrotic protein and exerts pro- as well as anti-cancerogenic activities. Our study aimed to correlate hepatocyte BAMBI protein levels in hepatocellular carcinoma (HCC) with T stage, lymph node invasion, vessel invasion, grading, tumor size and Union for International Cancer Control (UICC) stage, as well as with liver inflammation and fibrosis stages. Methods: Hepatocyte BAMBI protein expression was assessed by immunohistochemistry in HCC tissues of 320 patients and non-tumor tissues of 51 patients. Results: In the HCC tissues of the whole cohort and sex-specific analysis, BAMBI protein was not related to T stage, vessel invasion, lymph node invasion, histologic grade, UICC stage and tumor size. Accordingly, BAMBI was not associated with overall survival, recurrence-free and metastasis-free survival. BAMBI protein levels in tumor and non-tumor tissues were not related to inflammation and fibrosis grade. BAMBI protein levels in HCC tissues and non-tumor tissues from HCC patients, which were analyzed by immunoblot in a small cohort and by immunohistochemistry in the tissues of patients described above, were similar. Notably, BAMBI protein was low-abundant in HCC tissues of hepatitis C virus (HCV) compared to hepatitis B virus (HBV)-infected patients with comparable disease severity. Immunoblot analysis revealed reduced BAMBI protein in non-tumor tissues of patients with HCV in comparison to patients with HBV and normal human liver tissues. Conclusions: In summary, this analysis showed that hepatocyte BAMBI protein levels of patients with HCC are related to HCV infection rather than the severity of the underlying liver disease and cancer staging.
Mitochondrial Dysfunction and Ion Imbalance in a Rat Model of Hemodialysis-Induced Myocardial Stunning
Authors: Nie Yuxin , Lin Liyu , Yang Qiang , Hu Jiachang , Sun Minmin , Xiang Fangfang , Cao Xuesen , Yu Jinbo , Wang Yaqiong , Teng Jie , Ding Xiaoqiang , Shen Bo , Zhang Zhen
Published: October 2024

Background/Objectives: Hemodialysis-induced myocardial stunning (HIMS) is a frequent complication in patients undergoing maintenance hemodialysis, characterized by transient left ventricular dysfunction due to ischemic episodes. Mitochondrial dysfunction and fluctuations in key ions such as potassium (K+) and calcium (Ca2+) are implicated in the pathogenesis of HIMS. This study aims to investigate the role of mitochondrial dysfunction and the protective potential of mitochondrial ATP-sensitive potassium channels (mitoKATP) in mitigating HIMS. Methods: A 5/6 nephrectomy rat model was established to mimic chronic kidney disease and the subsequent HIMS. The effects of mitoKATP channel modulators were evaluated by administering diazoxide (DZX), a mitoKATP opener, and 5-hydroxydecanoate (5-HD), a mitoKATP blocker, before hemodialysis. Mitochondrial function was assessed by measuring membrane potential, ATP synthase activity, and intramitochondrial Ca2+ levels. Myocardial function was evaluated using speckle tracking echocardiography. Results: Rats undergoing hemodialysis exhibited significant reductions in left ventricular strain and synchrony. DZX administration significantly improved mitochondrial function and reduced myocardial strain compared to controls. Conversely, 5-HD worsened mitochondrial swelling and disrupted myocardial function. Higher K+ and Ca2+ concentrations in the dialysate were associated with improved mitochondrial energy metabolism and myocardial strain. Conclusions: Mitochondrial dysfunction and ion imbalances during hemodialysis are key contributors to HIMS. The activation of mitoKATP channels provides mitochondrial protection and may serve as a potential therapeutic strategy to mitigate HIMS.
Absolute Quantitative Targeted Monitoring of Potential Plasma Protein Biomarkers: A Pilot Study on Healthy Individuals
Authors: Kononikhin Alexey S. , Starodubtseva Natalia L. , Brzhozovskiy Alexander G. , Tokareva Alisa O. , Kashirina Daria N. , Zakharova Natalia V. , Bugrova Anna E. , Indeykina Maria I. , Pastushkova Liudmila Kh. , Larina Irina M. , Mitkevich Vladimir A. , Makarov Alexander A. , Nikolaev Evgeny N.
Published: October 2024

Background/Objectives: The development of blood tests for the early detection of individual predisposition to socially significant diseases remains a pressing issue. Methods: In this pilot study, multiple reaction monitoring mass spectrometry (MRM-MS) with a BAK-270 assay was applied for protein concentrations analysis in blood plasma from 21 healthy volunteers of the European cohort. Results: The levels of 138 plasma proteins were reliably and precisely quantified in no less than 50% of samples. The quantified proteins included 66 FDA-approved markers of cardiovascular diseases (CVD), and other potential biomarkers of pathologies such as cancer, diabetes mellitus, and Alzheimer’s disease. The analysis of individual variations of the plasma proteins revealed significant differences between the male (11) and female (10) groups. In total, fifteen proteins had a significantly different concentration in plasma; this included four proteins that exhibited changes greater than ±1.5-fold, three proteins (RBP4, APCS, and TTR) with higher levels in males, and one (SHBG) elevated in females. The obtained results demonstrated considerable agreement with the data collected from 20 samples of a North American cohort, which were analyzed with the similar MRM assay. The most significant differences between the cohorts of the two continents were observed in the level of 42 plasma proteins (including 24 FDA markers), of which 17 proteins showed a ≥1.5-fold change, and included proteins increased in North Americans (APOB, CRTAC1, C1QB, C1QC, C9, CRP, HP, IGHG1, IGKV4-1, SERPING1, RBP4, and AZGP1), as well as those elevated in Europeans (APOF, CD5L, HBG2, SELPLG, and TNA). Conclusions: The results suggest a different contribution of specific (patho)physiological pathways (e.g., immune system and blood coagulation) to the development of socially significant diseases in Europeans and North Americans, and they should be taken into account when refining diagnostic panels.
miRNA in Machine-Learning-Based Diagnostics of Oral Cancer
Authors: Li Xinghang , Kouznetsova Valentina L. , Tsigelny Igor F.
Published: October 2024

Background: MicroRNAs (miRNAs) are crucial regulators of gene expression, playing significant roles in various cellular processes, including cancer pathogenesis. Traditional cancer diagnostic methods, such as biopsies and histopathological analyses, while effective, are invasive, costly, and require specialized skills. With the rising global incidence of cancer, there is a pressing need for more accessible and less invasive diagnostic alternatives. Objective: This research investigates the potential of machine-learning (ML) models based on miRNA attributes as non-invasive diagnostic tools for oral cancer. Methods and Tools: We utilized a comprehensive methodological framework involving the generation of miRNA attributes, including sequence characteristics, target gene associations, and cancer-specific signaling pathways. Results: The miRNAs were classified using various ML algorithms, with the BayesNet classifier demonstrating superior performance, achieving an accuracy of 95% and an area under receiver operating characteristic curve (AUC) of 0.98 during cross-validation. The model’s effectiveness was further validated using independent datasets, confirming its potential clinical utility. Discussion: Our findings highlight the promise of miRNA-based ML models in enhancing early cancer detection, reducing healthcare burdens, and potentially saving lives. Conclusions: This study paves the way for future research into miRNA biomarkers, offering a scalable and adaptable diagnostic approach for various cancers.
The SUMO Family: Mechanisms and Implications in Thyroid Cancer Pathogenesis and Therapy
Authors: Jiaerken Bahejuan , Liu Wei , Zheng Jiaojiao , Qu Weifeng , Wu Qiao , Ai Zhilong
Published: October 2024

(1) Background: Small ubiquitin-like modifiers (SUMOs) are pivotal in post-translational modifications, influencing various cellular processes, such as protein localization, stability, and genome integrity. (2) Methods: This review explores the SUMO family, including its isoforms and catalytic cycle, highlighting their significance in regulating key biological functions in thyroid cancer. We discuss the multifaceted roles of SUMOylation in DNA repair mechanisms, protein stability, and the modulation of receptor activities, particularly in the context of thyroid cancer. (3) Results: The aberrant SUMOylation machinery contributes to tumorigenesis through altered gene expression and immune evasion mechanisms. Furthermore, we examine the therapeutic potential of targeting SUMOylation pathways in thyroid cancer treatment, emphasizing the need for further research to develop effective SUMOylation inhibitors. (4) Conclusions: By understanding the intricate roles of SUMOylation in cancer biology, we can pave the way for innovative therapeutic strategies to improve outcomes for patients with advanced tumors.
Chronically Increased Levels of Circulating Insulin Secondary to Insulin Resistance: A Silent Killer
Authors: Fazio Serafino , Bellavite Paolo , Affuso Flora
Published: October 2024

Despite all the progress made by science in the prevention and treatment of cardiovascular diseases and cancers, these are still the main reasons for hospitalizations and death in the Western world. Among the possible causes of this situation, disorders related to hyperinsulinemia and insulin resistance (Hyperin/IR) are still little-known topics. An analysis of the literature shows that this condition is a multiple risk factor for type 2 diabetes, cardiovascular diseases, cellular senescence and cancer, and neurodegenerative diseases. Hyperin/IR is progressively increasing worldwide, and its prevalence has now exceeded 50% of the general population and in overweight children. Asymptomatic or poorly symptomatic, it can last for many years before manifesting itself as diabetes, cardiovascular disease, neoplasm, cognitive deficit, or dementia, therefore leading to enormous social and healthcare costs. For these reasons, a screening plan for this pathology should be implemented for the purpose of identifying people with Hyperin/IR and promptly starting them on preventive treatment.
Stable Walking of a Biped Robot Controlled by Central Pattern Generator Using Multivariate Linear Mapping
Authors: Wu Yao , Tang Biao , Tang Jiawei , Qiao Shuo , Pang Xiaobing , Guo Lei
Published: October 2024

In order to improve the walking stability of a biped robot in multiple scenarios and reduce the complexity of the Central Pattern Generator (CPG) model, a new CPG walking controller based on multivariate linear mapping was proposed. At first, in order to establish a dynamics model, the lower limb mechanical structure of the biped robot was designed. According to the Lagrange and angular momentum conservation method, the hybrid dynamic model of the biped robot was established. The initial value of the robot’s passive walking was found by means of Poincaré mapping and cell mapping methods. Then, a multivariate linear mapping model was established to form a new lightweight CPG model based on a Hopf oscillator. According to the parameter distribution of the new CPG model, a preliminary parameter-tuning idea was proposed. At last, the joint simulation of MATLAB and V-REP shows that the biped robot based on the new CPG control has a stable periodic gait in flat and uphill scenes. The proposed method could improve the stability and versatility of bipedal walking in various environments and can provide general CPG generation and a tuning method reference for robotics scholars.
Biofeedback-Based Closed-Loop Phytoactuation in Vertical Farming and Controlled-Environment Agriculture
Authors: Kernbach Serge
Published: October 2024

This work focuses on biohybrid systems—plants with biosensors and actuating mechanisms that enhance the ability of biological organisms to control environmental parameters, to optimize growth conditions or to cope with stress factors. Biofeedback-based phytoactuation represents the next step of development in hydroponics, vertical farming and controlled-environment agriculture. The sensing part of the discussed approach uses (electro)physiological sensors. The hydrodynamics of fluid transport systems, estimated electrochemically, is compared with sap flow data provided by heat-based methods. In vivo impedance spectroscopy enables the discrimination of water, nutrient and photosynthates in the plant stem. Additionally to plant physiology, the system measures several air/soil and environmental parameters. The actuating part includes a multi-channel power module to control phytolight, irrigation, fertilization and air/water preparation. We demonstrate several tested in situ applications of a closed-loop control based on real-time biofeedback. In vertical farming, this is used to optimize energy and water consumption, reduce growth time and detect stress. Biofeedback was able to reduce the microgreen production cycle from 7 days to 4–5 days and the production of wheatgrass from 10 days to 7–8 days, and, in combination with biofeedback-based irrigation, a 30% increase in pea biomass was achieved. Its energy optimization can reach 25–30%. In environmental monitoring, the system performs the biological monitoring of environmental pollution (a low concentration of O3) with tomato and tobacco plants. In AI research, a complex exploration of biological organisms, and in particular the adaptation mechanisms of circadian clocks to changing environments, has been shown. This paper introduces a phytosensor system, describes its electrochemical measurements and discusses its tested applications.
Explorative Binary Gray Wolf Optimizer with Quadratic Interpolation for Feature Selection
Authors: Zhang Yijie , Cai Yuhang
Published: October 2024

The high dimensionality of large datasets can severely impact the data mining process. Therefore, feature selection becomes an essential preprocessing stage, aimed at reducing the dimensionality of the dataset by selecting the most informative features while improving classification accuracy. This paper proposes a novel binary Gray Wolf Optimization algorithm to address the feature selection problem in classification tasks. Firstly, the historical optimal position of the search agent helps explore more promising areas. Therefore, by linearly combining the best positions of the search agents, the algorithm’s exploration capability is increased, thus enhancing its global development ability. Secondly, the novel quadratic interpolation technique, which integrates population diversity with local exploitation, helps improve both the diversity of the population and the convergence accuracy. Thirdly, chaotic perturbations (small random fluctuations) applied to the convergence factor during the exploration phase further help avoid premature convergence and promote exploration of the search space. Finally, a novel transfer function processes feature information differently at various stages, enabling the algorithm to search and optimize effectively in the binary space, thereby selecting the optimal feature subset. The proposed method employs a k-nearest neighbor classifier and evaluates performance through 10-fold cross-validation across 32 datasets. Experimental results, compared with other advanced algorithms, demonstrate the effectiveness of the proposed algorithm.
Performance Comparison of Bio-Inspired Algorithms for Optimizing an ANN-Based MPPT Forecast for PV Systems
Authors: Rojas-Galván Rafael , García-Martínez José R. , Cruz-Miguel Edson E. , Álvarez-Alvarado José M. , Rodríguez-Resendiz Juvenal
Published: October 2024

This study compares bio-inspired optimization algorithms for enhancing an ANN-based Maximum Power Point Tracking (MPPT) forecast system under partial shading conditions in photovoltaic systems. Four algorithms—grey wolf optimizer (GWO), particle swarm optimization (PSO), squirrel search algorithm (SSA), and cuckoo search (CS)—were evaluated, with the dataset augmented by perturbations to simulate shading. The standard ANN performed poorly, with 64 neurons in Layer 1 and 32 in Layer 2 (MSE of 159.9437, MAE of 8.0781). Among the optimized approaches, GWO, with 66 neurons in Layer 1 and 100 in Layer 2, achieved the best prediction accuracy (MSE of 11.9487, MAE of 2.4552) and was computationally efficient (execution time of 1198.99 s). PSO, using 98 neurons in Layer 1 and 100 in Layer 2, minimized MAE (2.1679) but had a slightly longer execution time (1417.80 s). SSA, with the same neuron count as GWO, also performed well (MSE 12.1500, MAE 2.7003) and was the fastest (987.45 s). CS, with 84 neurons in Layer 1 and 74 in Layer 2, was less reliable (MSE 33.7767, MAE 3.8547) and slower (1904.01 s). GWO proved to be the best overall, balancing accuracy and speed. Future real-world applications of this methodology include improving energy efficiency in solar farms under variable weather conditions and optimizing the performance of residential solar panels to reduce energy costs. Further optimization developments could address more complex and larger-scale datasets in real-time, such as integrating renewable energy sources into smart grid systems for better energy distribution.
Microbial Protein and Metabolite Profiles of Klebsiella oxytoca M5A1 in a Bubble Column Bioreactor
Authors: Ayodele Tawakalt , Liadi Musiliu , Tijani Abodunrin Tirmidhi , Alarape Kudirat , Bitrus Christiana , Clementson Clairmont L. , Hammed Ademola
Published: October 2024

The production of microbial proteins (MPs) has emerged as a critical focus in biotechnology, driven by the need for sustainable and scalable alternatives to traditional protein sources. This study investigates the efficacy of two experimental setups in producing MPs using the nitrogen-fixing bacterium Klebsiella oxytoca M5A1. K. oxytoca M5A1, known for its facultative anaerobic growth and capability to fix atmospheric nitrogen, offers a promising avenue for environmentally friendly protein production. This research compares the performance of a simple bubble column (BC) bioreactor, which promotes efficient mixing and cross-membrane gas transfer, with static fermentation, a traditional method lacking agitation and aeration. The study involved the parallel cultivation of K. oxytoca M5A1 in both systems, with key parameters such as microbial growth, glucose utilization, protein concentration, and metabolite profiles monitored over a 48 h period. The results indicate that the BC bioreactor consistently outperformed static fermentation regarding the growth rate, protein yield, and glucose utilization efficiency. The BC exhibited a significant increase in protein production, reaching 299.90 µg/mL at 48 h, compared to 219.44 µg/mL in static fermentation. The organic acid profile reveals both synthesis and utilization regimes of varying patterns. These findings highlight the advantages of the BC bioreactor for MP production, particularly its ability to maintain aerobic conditions that support higher growth and yield.
Beta-Amyloid and Its Asp7 Isoform: Morphological and Aggregation Properties and Effects of Intracerebroventricular Administration
Authors: Ushakova Valeriya , Zorkina Yana , Abramova Olga , Kuanaeva Regina , Barykin Evgeny , Vaneev Alexander , Timoshenko Roman , Gorelkin Peter , Erofeev Alexander , Zubkov Eugene , Valikhov Marat , Gurina Olga , Mitkevich Vladimir , Chekhonin Vladimir , Morozova Anna
Published: October 2024

Background/Objectives: One of the hallmarks of Alzheimer’s disease (AD) is the accumulation of aggregated beta-amyloid (Aβ) protein in the form of senile plaques within brain tissue. Senile plaques contain various post-translational modifications of Aβ, including prevalent isomerization of Asp7 residue. The Asp7 isomer has been shown to exhibit increased neurotoxicity and induce amyloidogenesis in brain tissue of transgenic mice. The toxicity of Aβ peptides may be partly mediated by their structure and morphology. In this respect, in this study we analyzed the structural and aggregation characteristics of the Asp7 isoform of Aβ42 and compared them to those of synthetic Aβ42. We also investigated the effects of intracerebroventricular (i.c.v.) administration of these peptides, a method often used to induce AD-like symptoms in rodent models. Methods: Atomic force microscopy (AFM) was conducted to compare the morphological and aggregation properties of Aβ42 and Asp7 iso-Aβ42. The effects of i.c.v. stereotaxic administration of the proteins were assessed via behavioral analysis and reactive oxygen species (ROS) estimation in vivo using a scanning ion-conductance microscope with a confocal module. Results: AFM measurements revealed structural differences between the two peptides, most notably in their soluble toxic oligomeric forms. The i.c.v. administration of Asp7 iso-Aβ42 induced spatial memory deficits in rats and elevated oxidative stress levels in vivo, suggesting a potential of ROS in the pathogenic mechanism of the peptide. Conclusions: The findings support the further investigation of Asp7 iso-Aβ42 in translational research on AD and suggest its involvement in neurodegenerative processes.
The Impact of Short-Form Video and Optimistic Bias on Engagement in Oral Health Prevention: Integrating a KAP Model
Authors: Chung Donghwa , Wang Jiaqi , Meng Yanfang
Published: October 2024

College students are recognized as a demographic particularly susceptible to higher oral health risks due to irregular and unhealthy habits. While previous research has underscored these risks through descriptive studies within this group, a significant gap persists in the literature regarding the impact of contemporary media, specifically oral-health-related content, on the engagement in oral health prevention among Chinese college students. To address this gap, this study, guided by the extended knowledge–attitude–practice (KAP) theory model, explores the direct, mediated, and serially mediated mechanisms through which exposure to oral health short-form videos on Douyin influences their participation in oral health prevention. An empirical cross-sectional online survey was conducted, with valid data (N = 421) analyzed using descriptive statistics and hierarchical regression. Mediation and serial mediation analyses were also performed using SPSS version 25.0. The analysis revealed that exposure to oral health short-form videos had a positive direct effect on both oral health knowledge and the reduction of optimistic bias among Chinese college students. Furthermore, a significant serial mediation effect of oral health knowledge and oral health attitude was identified. The findings underscore the substantial applicability and explanatory power of the extended KAP theory model in understanding engagement in oral health prevention.
The Effect of Job Skill Demands Under Artificial Intelligence Embeddedness on Employees’ Job Performance: A Moderated Double-Edged Sword Model
Authors: Chen Ningning , Zhao Xinan , Wang Lele
Published: October 2024

With the widespread application of AI technology, the skills and abilities required by employees in their work are undergoing fundamental changes, redefining the roles of employees. This research aims to explore the effect of job skill demands under AI embeddedness on well-being in organizations and job performance. Based on conservation of resources theory, this research randomly selected 479 employees from 8 companies in China using a time-lag method as samples, and conducted statistical analysis with ordinary least squares (OLS). This research found that, job skill demands under AI embeddedness will both increase employees’ competency needs, promoting their well-being in organizations and job performance and decrease employees’ job embeddedness, inhibiting their well-being in organizations and job performance. Meanwhile, technological anxiety moderated the impact of job skill demands under AI embeddedness on job embeddedness.
Simulation of Coherent Excavator Operations in Earthmoving Tasks Based on Reinforcement Learning
Authors: Liu Yongyue , Wang Yaowu , Zhou Zhenzong
Published: October 2024

Earthwork operations are critical to construction projects, with their safety and efficiency influenced by factors such as operator skill and working hours. Pre-construction simulation of these operations is essential for optimizing outcomes, providing key training for operators and improving safety awareness and operational efficiency. This study introduces a hierarchical cumulative reward mechanism that decomposes complex operational behaviors into simple, fundamental actions. The mechanism prioritizes reward function design elements, including order, size, and form, thus simplifying excavator operation simulation using reinforcement learning (RL) and enhancing policy network reusability. A 3D model of a hydraulic excavator was constructed with six degrees of freedom—comprising the boom, arm, bucket, base, and left/right tracks. The Proximal Policy Optimization (PPO) algorithm was applied to train four basic behaviors: scraping, digging, throwing, and turning back. Motion simulation was successfully achieved using diggable terrain resources. Results demonstrate that the simulated excavator, powered by RL neural networks, can perform coordinated actions and maintain smooth operational performance. This research offers practical implications by rapidly illustrating the full operational process before construction, delivering immersive movies, and enhancing worker safety and operational efficiency.
Inversion Analysis for Thermal Parameters of Mass Concrete Based on the Sparrow Search Algorithm Improved by Mixed Strategies
Authors: Wang Yang , Gao Yang , Zhang Kaixing , Zhuang Mei-Ling , Xu Runze , Yan Xiumin , Wang Youzhi
Published: October 2024

In the traditional mass concrete temperature field calculation, the accuracy of the thermal parameters is extremely important. However, the actual thermal parameters of mass concrete may have some errors with the laboratory-measured values or specification values due to the site ambient temperature, concrete surface insulation measures, cooling water flow, etc. Therefore, it can be combined with the measured temperature of the field temperature sensors using the sparrow search algorithm (SSA) for the inverse analysis of thermal parameters. Firstly, to address the problem that SSA has low convergence accuracy and easily falls into local optimum, a mixed strategy was adopted to improve the algorithm, including Logistic Chaos mapping initialization of the population, the introduction of adaptive weighting factors, and the use of the Cauchy mutation strategy. Then, the performance test was carried out to compare the performance of the algorithm with three different intelligent algorithms and reflect the superiority of the SSA that was improved by mixed strategies (SSAIMSs). Finally, the proposed method was applied to the thermal parameter inversion of a mass concrete pile cap. The inversion results demonstrated that SSAIMSs can improve the accuracy and speed of thermal parameter inversion, and the calculated results of the thermal parameters and temperatures obtained using the SSAIMSs matched well with the measured results in the field, which can meet the accuracy requirements of the actual engineering.
Construction and Optimization Strategies for Rural Residential Spatial Models Based on the Concept of Resource Metabolism: A Case Study of Rural Areas in the Shandong Plain
Authors: Zhou Zhongkai , Liu Meng , Zhao Jilong , Li Chaoxian
Published: October 2024

Rural communities can be conceptualized as spatial organisms interconnected by optimized resource utilization systems. Investigating the efficient utilization of rural resources and spatial construction methods grounded in resource metabolism is a pivotal step toward achieving the ecological transformation of rural spaces. This paper examined rural settlements in the Shandong Plain as a case study, exploring the relationships among three scales: village, neighborhoods, and courtyards. This analysis was based on elucidating the interaction mechanisms between “space and resource” and the integration of key resources and spatial elements. From the perspective of resource circulation and metabolism, this study aimed to elucidate the equilibrium of each resource element within three resource metabolism subsystems: the agricultural production system (core element), the ecological technology system (technological link), and the human life system (spatial carrier) in Shandong Plain’s villages, considering general climatic conditions. To achieve this, this research utilized the resource production volume, the utilization and transformation volume of resource metabolism technology facilities per unit area, and the average per capita resource consumption as fundamental measurement units. The concept of a rationing relationship is introduced to clarify resource allocation. Combining the aforementioned research on spatial resource metabolism in ecological villages in Shandong Province with the material flow analysis method, this study constructed a bottom–up spatial model of resource metabolism at three scales, courtyards, neighborhoods, and villages, under various resource metabolism scenarios. This study is anticipated to significantly contribute to the theoretical understanding of rural habitat environments, offering novel methods and perspectives for constructing ecological rural settlements.
A Comprehensive Review of Thermal Transmittance Assessments of Building Envelopes
Authors: Song Ahhyun , Kim Yeeun , Hwang Sangjun , Shin Minjae , Lee Sanghyo
Published: October 2024

Improving the energy efficiency of buildings is an important element of the effort to address global warming. The thermal performance of building envelopes is the most important thermal and physical property affecting energy performance. Therefore, identifying the thermal performance of a building envelope is essential to applying effective energy-saving measures. The U-value is a quantitative indicator of the thermal performance of the building envelope quantitatively. Methods for determining the U-value are largely classified into passive methods, which use building information without measurement campaigns, and active methods, which conduct in situ measurements. This paper reviews and evaluates the most commonly used methods and experimental results of previous studies to determine the actual U-value of a building envelope. Accordingly, this paper focuses solely on field measurement studies, excluding laboratory measurements. Comparing the existing methods used to determine the U-value can help researchers choose appropriate field measurement methods and future research directions.
BIM and IFC Data Readiness for AI Integration in the Construction Industry: A Review Approach
Authors: Du Sang , Hou Lei , Zhang Guomin , Tan Yongtao , Mao Peng
Published: October 2024

Building Information Modelling (BIM) has been increasingly integrated with Artificial Intelligence (AI) solutions to automate building construction processes. However, the methods for effectively transforming data from BIM formats, such as Industry Foundation Classes (IFC), into formats suitable for AI applications still need to be explored. This paper conducts a Systematic Literature Review (SLR) following the PRISMA guidelines to analyse current data preparation approaches in BIM applications. The goal is to identify the most suitable methods for AI integration by reviewing current data preparation practices in BIM applications. The review included a total of 93 articles from SCOPUS and WoS. The results include eight common data types, two data management frameworks, and four primary data conversion methods. Further analysis identified three barriers: first, the IFC format’s lack of support for time-series data; second, limitations in extracting geometric information from BIM models; and third, the absence of established toolchains to convert IFC files into usable formats. Based on the evidence, the data readiness is at an intermediate level. This research may serve as a guideline for future studies to address the limitations in data preparation within BIM for AI integration.
Residential Care Facilities for Users with Alzheimer’s Disease: Characterisation of Their Architectural Typology
Authors: Quesada-García Santiago , Valero-Flores Pablo , Lozano-Gómez María
Published: October 2024

The design and construction of residences for persons with Alzheimer’s disease (AD) have been based on the recommendations of design guides, the results of empirical tests with samples of the population, and the experience of architects and planners. The reiteration of certain patterns, criteria, and guidelines has given rise to a new type of building that has not yet been explicitly described. The aim of this paper is to determine the main characteristics of this typology. This research is based on a critical review methodology, analysing 30 care homes built over the last four decades across various global contexts. Detailed surveys of plans, projects, and buildings were carried out, allowing a comparative analysis of the architectural attributes to determine the most influential parameters for these buildings. The results indicate that environments designed with safety, accessibility, and opportunities for social interaction in mind—and, above all, those that are personalised to the needs of this collective—significantly enhance the behaviour, emotional state, and cognitive state of their residents. The main theoretical contributions include identifying and stating the key features of this type, such as small scale, basic cell housing, comprehensible organisation, and sensory stimulation of spaces, among others. The breakthrough of this study that differentiates it from other works in this field is that it provides concrete guidelines to approach the planning, design, and construction of these kinds of residences. The significance of this research lies in the definition of this unique typology, which is not characterised by its morphology, shape, or formal composition but rather focused on promoting an adequate cognitive and physiological reception of the space by the users. This building concept has important management implications, as its construction must provide for and integrate specific care services in a residential setting for people with AD.
The Impact of Cool and Warm Color Tones in Classrooms on the Perceived Emotions of Elementary School Students in Northwest China
Authors: Sun Yazhen , Qi Na , Zhan Jie , Yin Jie
Published: October 2024

Although it has been shown that color can influence mental health and behavior, few studies have discussed the effects of cool and warm colors in classrooms on the perceived emotions of elementary school students. In this study, we investigated the emotional changes of elementary school students in Yinchuan City, Northwest China in classrooms with cool and warm color tones. By using the Positive and Negative Affect Scale for Children (PANAS-C), the emotions of 123 third- to sixth-grade students in classrooms with cool and warm color tones were measured. We found the following conclusions: (1) Overall, the emotional responses of the subjects in both the cool- and warm-colored classrooms showed a tendency for positive emotions to be higher than negative emotions. (2) There was no significant difference between the effects of cool and warm colors on the overall emotion of elementary school students, but there were significant differences in specific emotions; Compared to warm colors, cool colors had a more significant effect on increasing feelings of calm (β = −0.365, p = 0.041). Compared to cool colors, warm colors were more likely to cause participants to feel mad (β = 0.186, p = 0.099). (3) The effects of cool and warm colors on students’ emotions differed significantly by gender and grade level. Cool and warm color tones had a significantly greater positive impact on females. In contrast, cool and warm colors had a more pronounced effect on males’ negative emotions. In addition, we found that grade level was significantly negatively correlated with overall emotion (β = −0.696, p < 0.001), with lower grades perceiving emotion more positively than higher grades. These findings provide important insights into the spatial design of elementary school classrooms and provide valuable comparative data for studies in different regional and cultural contexts, further enriching the empirical support of color psychology theory.
The Non-Image-Forming Effects of Daylight: An Analysis for Design Practice Purposes
Authors: Chen Ting , Zhang Zhiyuan
Published: October 2024

Daylight plays a crucial role in human health, and as research into its effects expands, it is essential for designers to estimate the non-image-forming impacts of various daylighting and lighting strategies. This allows them to create indoor environments that are both pleasant and comfortable. To support this, daylight measurements were taken in five Chinese cities, focusing on spectral power distribution, correlated color temperature, and illuminance. The study calculated the non-image-forming effects of daylight exposure using metrics like melanopic Equivalent Daylight Illuminance and Circadian Light. A key finding was the development of the action factor SAI, which estimates the potential non-image-forming effects of light in built environments. This factor serves as a proxy for understanding how non-image-forming effects relate to correlated color temperatures. Additionally, the research suggests the possibility of creating a time-variational daylighting and lighting strategy with four distinct periods of non-image-forming effects throughout a 24 h day. These insights could be valuable for architects and designers in optimizing indoor lighting systems.
Decision-Making Amid Economic Uncertainty: Exploring the Key Considerations of Commercial Property Investors
Authors: Ahiadu Albert Agbeko , Abidoye Rotimi Boluwatife , Yiu Tak Wing
Published: October 2024

This study explored the key considerations of commercial property investors acting under conditions of economic uncertainty across the following three dimensions: market fundamentals, institutional, and behavioural factors. Over the past few decades, a series of exogenous shocks to the global economy has impacted property performance, investment volumes, and investor perceptions. Acknowledging that uncertainty further complicates investment decision-making, a mixed-methods research approach was adopted to examine the perspectives of 5 experts and 412 property investors. The findings revealed that, while most investors express negative responses to uncertainty and adopt more cautious attitudes, others are more aggressive and attempt to capitalise on emerging opportunities. Market fundamentals are not the only key consideration; access to information and investors’ behaviour all impact how decisions are made under these conditions. In particular, wealthy and more experienced investors make more comprehensive decisions, considering all three dimensions, while aggressive investors may disregard data in favour of intuition. Behavioural biases such as the bandwagon effect and fear of missing out (FOMO) all influence decisions and are sometimes exacerbated by media narratives. Practically, these considerations underscore the complexity of decision-making under conditions of uncertainty and how different investors attempt to navigate market volatility.