bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysing Virtual Labs Through Integrated Multi-Channel Eye-Tracking Technology: A Proposal for an Explanatory Fit Model
Authors: Sáiz-Manzanares María Consuelo , Marticorena-Sánchez Raúl , Sáez-García Javier , González-Díez Irene
Published: October 2024

This study deals with an analysis of the cognitive load indicators produced in virtual simulation tasks through supervised and unsupervised machine learning techniques. The objectives were (1) to identify the most important cognitive load indicators through the use of supervised and unsupervised machine learning techniques; (2) to study which type of task presentation was most effective at reducing the task’s intrinsic load and increasing its germane load; and (3) to propose an explanatory model and find its fit indicators. We worked with a sample of 48 health sciences and biomedical engineering students from the University of Burgos (Spain). The results indicate that being able to see the task before performing it increases the germane load and decreases the intrinsic load. Similarly, allowing students a choice of presentation channel for the task respects how they process information. In addition, indicators of cognitive load were found to be grouped into components of position, speed, psychogalvanic response, and skin conductance. An explanatory model was proposed and obtained acceptable fit indicators.
Validity of Force and Power Measures from an Integrated Rotary Encoder in a HandyGym Portable Flywheel Exercise Device
Authors: Illera-Domínguez Víctor , Font-Aragonés Xavier , Toro-Román Víctor , Díaz-Alejandre Samuel , Pérez-Chirinos Carla , Albesa-Albiol Lluís , González-Millán Sara , Fernández-Valdés Bruno
Published: October 2024

Introduction: This study aimed to evaluate the validity of the HandyGym portable flywheel device with an integrated rotary encoder in measuring force and power during iso-inertial exercises compared to a traditional reference system. Methods: In total, 10 trained volunteers (3 women, 7 men; age 25.2 ± 3.8 years) performed half-squats with five different load configurations using the HandyGym device. Concurrent measurements were obtained from HandyGym’s rotary encoder and a criterion system (MuscleLab 6000 strain gauge and linear encoder). Five load configurations were tested, with 15 repetitions recorded per condition. The validity of the HandyGym measurements was assessed through mean bias, typical error of estimation (TEE), and Pearson correlation coefficients, with Bland–Altman plots used to analyze the agreement between the two systems. Results: The HandyGym showed high correlations with the reference system for both force (r = 0.76–0.90) and power (r = 0.60–0.94). However, systematic biases were observed, with the HandyGym consistently underestimating force and power at lower loads and overestimating power at higher loads. The TEE values indicated moderate to large errors, particularly in power measurements. Conclusion: The HandyGym provides valid force measurements with moderate bias, suitable for general monitoring. However, power measurements are less consistent, especially at higher loads, limiting the device’s utility for precise assessments. Adjustments or corrections may be necessary for accurate application in professional contexts.
Fuel Efficiency Optimization in Adaptive Cruise Control: A Comparative Study of Model Predictive Control-Based Approaches
Authors: Borneo Angelo , Miretti Federico , Misul Daniela Anna
Published: October 2024

This work investigates the fuel efficiency potential of Adaptive Cruise Control (ACC) systems, focusing on two optimization-based control approaches for internal combustion engine (ICE) vehicles. In particular, this study compares two model predictive control (MPC) designs. In the first approach, a strictly quadratic cost is adopted, and fuel consumption is indirectly minimized by adjusting the weights assigned to state tracking and control effort. In the second approach, a fuel consumption map is explicitly included in the MPC cost function, aiming to directly minimize it. Both approaches are compared to a globally optimal benchmark obtained with dynamic programming. Although these methods have been discussed in the literature, no systematic comparison of their relative performance has been conducted, which is the primary contribution of this article. The results demonstrate that, with proper tuning, the simpler quadratic approach can achieve comparable fuel savings to the approach with explicit fuel consumption minimization, with a maximum variation of 0.5%. These results imply that the first alternative is more suitable for online implementation, due to the more favorable characteristics of the associated optimization problem.
Recent Advances in Black Silicon Surface Modification for Enhanced Light Trapping in Photodetectors
Authors: Alsolami Abdulrahman , Hussain Hadba , Noor Radwan , AlAdi Nourah , Almalki Nada , Kurdi Abdulaziz , Tabbakh Thamer , Zaman Adnan , Alfihed Salman , Wang Jing
Published: October 2024

The intricate nanostructured surface of black silicon (BSi) has advanced photodetector technology by enhancing light absorption. Herein, we delve into the latest advancements in BSi surface modification techniques, specifically focusing on their profound impact on light trapping and resultant photodetector performance improvement. Established methods such as metal-assisted chemical etching, electrochemical etching, reactive ion etching, plasma etching, and laser ablation are comprehensively analyzed, delving into their mechanisms and highlighting their respective advantages and limitations. We also explore the impact of BSi on the emerging applications in silicon (Si)-based photodetectors, showcasing their potential for pushing the boundaries of light-trapping efficiency. Throughout this review, we critically evaluate the trade-offs between fabrication complexity and performance enhancement, providing valuable insights for future development in this rapidly evolving field. This knowledge on the BSi surface modification and its applications in photodetectors can play a crucial role in future implementations to substantially boost light trapping and the performance of Si-based optical detection devices consequently.
GBNSS: A Method Based on Graph Neural Networks (GNNs) for Global Biological Network Similarity Search
Authors: Wang Yi , Zhan Feng , Huang Cuiyu , Huang Yiran
Published: October 2024

Biological network similarity search plays a crucial role in the analysis of biological networks for human disease research and drug discovery. A biological network similarity search aims to efficiently identify novel networks biologically homologous to the query networks. Great progress has been achieved in biological network similarity searches. However, it remains a challenge to mine the biological network information fully to improve the accuracy of query results without increasing time overheads. In this study, we propose a biological network similarity search method based on graph neural networks named GBNSS, which combines topological and biological information (GO annotations) of biological networks into graph neural networks to find topologically and biologically similar biological networks in the database. Additionally, GBNSS is a topology-free biological network similarity search method with an arbitrary network structure. The experimental results on four benchmark datasets show that GBNSS outperforms the existing methods in terms of computational efficiency and search accuracy. Case studies further demonstrate that GBNSS is capable of searching similar networks in real-world biological networks.
Suitability of UR5 Robot for Robotic 3D Printing
Authors: Pollák Martin , Kočiško Marek , Grozav Sorin D. , Ceclan Vasile , Bogdan Alexandru D.
Published: October 2024

The present paper describes the measurement of the drift of unidirectional pose accuracy, repeatability, and static compliance of a collaborative robot employing a measurement methodology that relies on the description of a virtual ISO cube placed in the robot’s workspace. The measurements aimed to investigate and assess the suitability of the UR5 six-axis collaborative robot for its application in robotic 3D printing. An experimental laboratory measurement workstation was constructed to perform the measurements, and control measurements were performed. The measurements involved describing the TCP point of the robot tool at five measurement points located in a virtual ISO cube during a minimum of 30 repeated measurement cycles. A camera and six linear incremental sensors with assessment units were used for the measurements. The measurements were performed in compliance with the regulations of STN ISO 9283 standard for this type of measurement. As a result of the measurements, the technical specifications of the drift and static compliance of the controlled robotic arm were verified, and the results were compared with the values specified by the manufacturer. Following the measurements and assessment of the results, it was possible to assess the suitability of the used UR5 robotic arm for its application in robotic 3D printing and to propose possible recommendations for the calibration of the robot and the process settings of the printing system for the production of objects using FDM technology.
Acute Effects of Overload Running on Physiological and Biomechanical Variables in Trained Trail Runners
Authors: Cartón-Llorente Antonio , Rubio-Peirotén Alberto , Cardiel-Sánchez Silvia , Díez-Martínez Pablo , Roche-Seruendo Luis Enrique , Jaén-Carrillo Diego
Published: October 2024

Background: The biomechanical and physiological adaptations to resisted running have been well documented in sprinting; however, their impact at submaximal speeds, such as those typical of long-distance running, remains unclear. This study aimed to evaluate the impact of running with a weighted vest, loaded with 5% and 10% of body mass, on the physiological and mechanical variables of trained trail runners. Methods: Fifteen male trail runners completed an incremental protocol to exhaustion on a treadmill with 0%, 5%, and 10% of their body mass (BM), in random order, with one week of separation between the tests. The maximality of the test was confirmed by measuring lactate concentrations at the end of the test. Oxygen consumption (V˙O2) and respiratory exchange ratio (RER) were recorded using a portable gas analyzer (Cosmed K5), and ventilatory thresholds 1 and 2 (VT1, VT2) were calculated individually. Running power was averaged for each speed stage using the Stryd device. Finally, the peak values and those associated with VT1 and VT2 for speed, power (absolute and normalized by body mass), V˙O2, RER, and the cost of transport (CoT) were included in the analysis. Results: One-way repeated-measures ANOVA revealed a detrimental effect of the extra load on maximum speed and speed at ventilatory thresholds (p ≤ 0.003), with large effect sizes (0.34–0.62) and a nonlinear trend detected in post hoc analysis. Conclusions: Using running power to control the intensity of effort while carrying extra weight provides a more stable metric than speed, particularly at aerobic intensities. Future research in trail running should investigate the effects of weighted vests across various terrains and slopes.
Evaluating the Current Situation of River and Lake Shoreline Planning and Utilization Using an Improved Matter-Element Extension Model
Authors: Wang Bo , Li Shihua , Yang Kang , Zhu Xinyu , Luo Fan
Published: October 2024

Based on the analysis of the influencing factors of the current planning and utilization of river and lake shorelines, an index system of the current planning and utilization of river and lake shorelines is constructed. Based on the triangular fuzzy number method and the improved CRITIC method, the evaluation indicators are weighted and analyzed and then integrated to obtain the combined weight. An improved matter-element extension model was constructed to evaluate the current situation of shoreline planning and utilization in typical regions. At the same time, the TOPSIS evaluation model and the cloud theory evaluation model were compared and analyzed to verify the accuracy of the model. The improved matter-element model accounts for indicator incompatibility and the uncertainty of evaluation boundaries, offering a clearer reflection of the planning and utilization status.
On the Use of Image Analysis for Hematocrit Evaluation in Dried Blood Spots
Authors: Daousani Chrysa , Kostić Nađa , Malenović Anđelija , Rmandić Milena , Dotsikas Yannis
Published: October 2024

Dried blood spots (DBSs) are formed by collecting a small sample of blood on specialized filter paper and allowing it to dry naturally. Various domains of life sciences and drug research extensively use DBSs as a sampling technique. The “Hematocrit (Ht) effect” affects assay bias, and several strategies have been put forth to deal with it, including the correction of quantified concentrations using an appropriate correction factor. The approach was previously applied, following the utilization of an image processing algorithm developed in Matlab® to derive a reliable equation correlating DBS areas to Ht% values. The present work looks more closely at the application of image analysis to the evaluation of Ht in DBS samples. Utilizing image analysis software, DBS samples with known Ht values were processed. Preparation of cards has followed a previously developed protocol for the appropriate formation of uniform area DBSs, irrespective of Ht. The resulting areas showed close resemblance to the respective theoretical areas calculated by applying the correlation equation. Following that, the equation was utilized to determine the Ht values for each sample, and a comprehensive comparison of measured versus calculated Ht was carried out using various statistical approaches for method comparison. The results demonstrated a strong correlation, suggesting the method’s viability in estimating Ht for unknown DBS samples.
Improving Workplace Safety and Health Through a Rapid Ergonomic Risk Assessment Methodology Enhanced by an Artificial Intelligence System
Authors: Ispășoiu Adrian , Milosan Ioan , Gabor Camelia
Published: October 2024

The comfort of a worker while performing any activity is extremely important. If that activity extends beyond a person’s capacity to withstand physical and psychological stress, the worker may suffer from both physical and mental ailments. Over time, if the stress persists, these conditions can become chronic diseases and can even be the cause of workplace accidents. In this research, a methodology was developed for the rapid assessment of ergonomic risks and for calculating the level of ergonomic comfort in the workplace. This methodology uses artificial intelligence through a specific algorithm and takes into account a number of factors that, when combined, can have a significant impact on workers. To achieve a more accurate simulation of a work situation or to evaluate an ongoing work situation, and to significantly correlate these parameters, we used logarithmic calculation formulas. To streamline the process, we developed software that performs these calculations, conducts a rapid assessment of ergonomic risks, estimates a comfort level, and proposes possible measures to mitigate the risks and effects on workers. To assist in diagnosing the work situation, we used a neural network with five neurons in the input layer, one hidden layer, and two neurons in the output layer. As a result, most work situations, in any industrial field, can be quickly analyzed and evaluated using this methodology. The use of this new analysis and diagnosis tool, implemented through this new research technology, is beneficial for employers and workers. Moreover, through further developments of this methodology, achieved by increasing the number of relevant input parameters for ergonomics and integrating advanced artificial intelligence systems, we aim to provide high precision in assessing ergonomic risk and calculating the level of ergonomic comfort.
Antimicrobial Activity of Chitosan from Different Sources Against Non-Saccharomyces Wine Yeasts as a Tool for Producing Low-Sulphite Wine
Authors: Tedesco Francesco , Pietrafesa Rocchina , Siesto Gabriella , Scieuzo Carmen , Salvia Rosanna , Falabella Patrizia , Capece Angela
Published: October 2024

Chitosan is used as an antimicrobial agent in different agri-food applications; in winemaking, the use of chitosan from Aspergillus niger is authorized, but other sources of chitin, and consequently of chitosan, are available, such as crustaceans and insects. This work investigates the antimicrobial efficiency of chitosan from crustaceans and insects (Hermetia illucens) against non-Saccharomyces yeasts in wine. For this aim, the first step was to evaluate the effect of crustacean chitosan, tested both alone and in combination with low sulphur dioxide (SO2) concentrations, on the cell viability of 20 non-Saccharomyces strains in the first step of fermentations inoculated with each strain. Furthermore, the strain resistance to crustacean- and insect-based chitosan was evaluated in agarized media, together with the addition of different antimicrobial concentrations. Finally, the efficiency of different antimicrobial treatments was evaluated during laboratory-scale fermentations inoculated with a selected S. cerevisiae strain. The tested strains exhibited medium/high resistance to the chitosan; in some cases, the behaviour varied in the function of species/strain, and only four strains exhibited different resistance levels, depending on the chitosan source. The addition of chitosan alone during fermentation inoculated with S. cerevisiae showed lower antimicrobial activity than SO2, but the combined use with SO2 showed a better effect than chitosan alone. The evaluation of the suitability of chitosan obtained from a sustainable source, such as insects, will allow us to give new information on the future applications of this natural compound for the production of wine with low sulphite content.
Colorectal Cancer Cell-Derived Extracellular Vesicles Promote Angiogenesis Through JAK/STAT3/VEGFA Signaling
Authors: Long Yuqing , Dan Yuxi , Jiang Yao , Ma Jing , Zhou Tao , Fang Liaoqiong , Wang Zhibiao
Published: October 2024

Background: Angiogenesis plays a crucial role in the growth of colorectal cancer (CRC). Recent studies have identified extracellular vesicles (EVs) in the tumor microenvironment as important mediators of cell-to-cell communication. However, the specific role and mechanisms of CRC-derived EVs in regulating tumor angiogenesis remain to be further investigated. Methods: EVs were isolated from the conditioned medium of the CRC cells using ultracentrifugation. We investigated the effects of HT-29-derived EVs on tumor growth and angiogenesis in a subcutaneous HT-29 CRC tumor model in mice. Additionally, we evaluated the impact of HT-29-derived EVs on the proliferation, migration, and tube formation of human umbilical vein endothelial cells (HUVECs). Subsequently, bioinformatics analysis was performed to identify relevant signaling pathways, and pathway inhibitors were used to block the activation of these pathways, aiming to elucidate their roles in angiogenesis. Results: We found that HT-29-derived EVs can promote tumor growth and angiogenesis in vivo, as well as significantly enhance the proliferation, migration, and tube formation of HUVECs. Bioinformatics analysis revealed that HT-29-derived EVs may regulate angiogenesis through the JAK/STAT3 signaling pathway. Specifically, we observed that CRC-derived EVs promoted the phosphorylation of STAT3 (p-STAT3) and the expression of VEGFA in the nucleus of HUVECs. Treatment with the STAT3 inhibitor Stattic reduced the nuclear expression of p-STAT3, which impaired its function as a transcription factor, thereby inhibiting VEGFA expression and the pro-angiogenic effects of CRC-derived EVs. Conclusions: EVs derived from CRC cells promote CRC tumor angiogenesis by regulating VEGFA through the JAK/STAT3 pathway in endothelial cells.
Trophic Position Stability of Benthic Organisms in a Changing Food Web of an Arctic Fjord Under the Pressure of an Invasive Predatory Snow Crab, Chionoecetes opilio
Authors: Zalota Anna K. , Dgebuadze Polina Yu. , Kiselev Alexander D. , Chikina Margarita V. , Udalov Alexey A. , Kondar Daria V. , Mishin Alexey V. , Tsurikov Sergey M.
Published: October 2024

The introduction of a large predatory snow crab, Chionoecetes opilio, into the Kara Sea is a unique situation where the impact of an invasive species affecting an otherwise undisturbed ecosystem can be observed unhindered by other ecosystem stressors. Trophic interactions are one of the principal relationships between animals and can help assess an ecosystem’s stability. The trophic positions and sources of organic material for the most common benthic species of Blagopoluchiya Bay sampled at different stages of the invasion were calculated using stable isotope analysis. The most pronounced changes in the trophic web occurred amongst the megabenthic species, where previously most abundant deposit-feeding ophiuroids have disappeared. However, the benthic species’ trophic position and primary production source preference did not change. A sea star, Urasterias lincki, remained the highest carnivore in the bay, and the invasive crab remained at a lower trophic level, showing higher omnivory in its diet. Any changes in the consumers’ prey items were within the same trophic level. Overall, active predators became one of the most abundant feeding mode groups. The average weighted trophic position of all megabenthic species increased to the third trophic level, where mostly secondary consumers remained.
Imidazole Headgroup Phospholipid Shows Asymmetric Distribution in Vesicles and Zinc-Dependent Esterase Activity
Authors: Sachet-Fernandez Gabriela , Hindley James W. , Ces Oscar , Woscholski Rüdiger
Published: October 2024

Artificial lipids have become increasingly important in generating novel nanoenzymes and nanoparticles. Imidazole has been well established as a versatile catalyst in synthetic chemistry and through its related amino acid histidine in enzymes. By exploiting the transphosphatidylation reaction of phospholipase D, the choline headgroup of phosphatidyl choline was exchanged for the imidazole moiety containing histidinol. Here, we introduce a novel phosphatidylhistidinol (PtdHisOH) lipid and characterise it with respect to its catalytic abilities and its ability to modulate vesicle size. Our data reveal a zinc-dependent esterase activity that was strongest in vesicles and micelles, with slower catalytic rates being observed in flat lipid presentation systems and two-phase systems, indicating the importance of surface presentation and curvature effects on the catalytic activity of PtdHisOH. Such lipids offer the opportunity to impart de novo catalytic functionality to self-assembled lipid systems such as synthetic cells, leading to the development of new technologies for biocatalysis applications.
Exposure to Metals, Pesticides, and Air Pollutants: Focus on Resulting DNA Methylation Changes in Neurodegenerative Diseases
Authors: Stoccoro Andrea , Coppedè Fabio
Published: October 2024

Individuals affected by neurodegenerative diseases, including Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS), are dramatically increasing worldwide. Thus, several efforts are being made to develop strategies for stopping or slowing the spread of these illnesses. Although causative genetic variants linked to the onset of these diseases are known, they can explain only a small portion of cases. The etiopathology underlying the neurodegenerative process in most of the patients is likely due to the interplay between predisposing genetic variants and environmental factors. Epigenetic mechanisms, including DNA methylation, are central candidates in translating the effects of environmental factors in genome modulation, and they play a critical role in the etiology of AD, PD, and ALS. Among the main environmental exposures that have been linked to an increased risk for these diseases, accumulating evidence points to the role of heavy metals, pesticides, and air pollutants. These compounds could trigger neurodegeneration through different mechanisms, mainly neuroinflammation and the induction of oxidative stress. However, increasing evidence suggests that they are also capable of inducing epigenetic alterations in neurons. In this article, we review the available literature linking exposure to metals, pesticides, and air pollutants to DNA methylation changes relevant to neurodegeneration.
Contribution of Protonation to the Dielectric Relaxation Arising from Bacteriopheophytin Reductions in the Photosynthetic Reaction Centers of Rhodobacter sphaeroides
Authors: Sipka Gábor , Maróti Péter
Published: October 2024

The pH dependence of the free energy level of the flash-induced primary charge pair P+IA− was determined by a combination of the results from the indirect charge recombination of P+QA− and from the delayed fluorescence of the excited dimer (P*) in the reaction center of the photosynthetic bacterium Rhodobacter sphaeroides, where the native ubiquinone at the primary quinone binding site QA was replaced by low-potential anthraquinone (AQ) derivatives. The following observations were made: (1) The free energy state of P+IA− was pH independent below pH 10 (–370 ± 10 meV relative to that of the excited dimer P*) and showed a remarkable decrease (about 20 meV/pH unit) above pH 10. A part of the dielectric relaxation of the P+IA− charge pair that is not insignificant (about 120 meV) should come from protonation-related changes. (2) The single exponential decay character of the kinetics proves that the protonated/unprotonated P+IA− and P+QA− states are in equilibria and the rate constants of protonation konH +koffH are much larger than those of the charge back reaction kback ~103 s−1. (3) Highly similar pH profiles were measured to determine the free energy states of P+QA− and P+IA−, indicating that the same acidic cluster at around QB should respond to both anionic species. This was supported by model calculations based on anticooperative proton distribution in the cluster with key residues of GluL212, AspL213, AspM17, and GluH173, and the effect of the polarization of the aqueous phase on electrostatic interactions. The larger distance of IA− from the cluster (25.2 Å) compared to that of QA− (14.5 Å) is compensated by a smaller effective dielectric constant (6.5 ± 0.5 and 10.0 ± 0.5, respectively). (4) The P* → P+QA− and IA−QA → IAQA− electron transfers are enthalpy-driven reactions with the exemption of very large (>60%) or negligible entropic contributions in cases of substitution by 2,3-dimethyl-AQ or 1-chloro-AQ, respectively. The possible structural consequences are discussed.
Biomass Demineralization and Pretreatment Strategies to Reduce Inhibitor Concentrations in Itaconic Acid Fermentation by Aspergillus terreus
Authors: Kennedy Gregory J. , Bowman Michael J. , Ascherl Kim L. , Nichols Nancy N. , Saha Badal C.
Published: October 2024

Itaconic acid (IA) is a platform chemical, derived from non-petroleum sources, produced through the fermentation of glucose by Aspergillus terreus. However, producing IA from alternative sugar sources (e.g., lignocellulose) has been shown to be problematic, requiring post-hydrolysis mitigation to allow growth and IA production by the fungus. It is well known that the side products of lignocellulosic biomass conversion to sugars act as microbial growth inhibitors. An uncommon feature of fungal organic acid fermentations is production inhibition caused by mineral ions in biomass hydrolysate after pretreatment and enzymatic hydrolysis. To minimize mineral introduction during pretreatment and hydrolysis, we determined the sources of growth and production inhibitors at each of these steps. Biomass demineralization and four pretreatment strategies were evaluated for inhibitor introduction. Dilution assays determined the approximate degree of inhibition for each hydrolysate. An ammonium hydroxide pretreatment of demineralized wheat straw presented the lowest concentration of inhibitors and concomitant lowest inhibition: subsequent fermentations produced 35 g L−1 IA from wheat straw hydrolysate (91 g L−1 sugar) without post-hydrolysis mitigation.
Potential Applications and Ethical Considerations for Artificial Intelligence in Traumatic Brain Injury Management
Authors: Beard Kryshawna , Pennington Ashley M. , Gauff Amina K. , Mitchell Kelsey , Smith Johanna , Marion Donald W.
Published: October 2024

Artificial intelligence (AI) systems have emerged as promising tools for rapidly identifying patterns in large amounts of healthcare data to help guide clinical decision making, as well as to assist with medical education and the planning of research studies. Accumulating evidence suggests AI techniques may be particularly useful for aiding the diagnosis and clinical management of traumatic brain injury (TBI)—a considerably heterogeneous neurologic condition that can be challenging to detect and treat. However, important methodological and ethical concerns with the use of AI in medicine necessitate close monitoring and regulation of these techniques as advancements continue. The purpose of this narrative review is to provide an overview of common AI techniques in medical research and describe recent studies on the possible clinical applications of AI in the context of TBI. Finally, the review describes the ethical challenges with the use of AI in medicine, as well as guidelines from the White House, the Department of Defense (DOD), the National Academies of Sciences, Engineering, and Medicine (NASEM), and other organizations on the appropriate uses of AI in research.
Collagen–Platelet-Rich Plasma Mixed Hydrogels as a pBMP2 Delivery System for Bone Defect Regeneration
Authors: Meglei Anastasiia Yurevna , Nedorubova Irina Alekseevna , Basina Viktoriia Pavlovna , Chernomyrdina Viktoria Olegovna , Nedorubov Andrey Anatolevich , Kuznetsova Valeriya Sergeevna , Vasilyev Andrey Vyacheslavovich , Kutsev Sergey Ivanovich , Goldshtein Dmitry Vadimovich , Bukharova Tatiana Borisovna
Published: October 2024

Background/Objectives: The replenishment of bone deficiency remains a challenging task in clinical practice. The use of gene-activated matrices (GAMs) impregnated with genetic constructs may be an innovative approach to solving this problem. The aim of this work is to develop collagen-based matrices with the addition of platelet-rich plasma, carrying polyplexes with the BMP2 gene, to study their biocompatibility and osteogenic potential in vitro and in vivo. Methods: The cytocompatibility of the materials during incubation with adipose-derived stem cells (ADSCs) was studied using the MTT test and fluorescent microscopy. Biocompatibility was assessed during intramuscular implantation, followed by histological analysis. Osteogenic differentiation was determined by the expressions of Alpl and Bglap using real-time PCR and extracellular matrix (ECM) mineralization by alizarin red staining. The efficiency of bone regeneration was studied using micro-CT and analysis of histological sections stained according to Masson. Results: After the incubation of ADSCs with GAS, significant increases in the expressions of the Alpl and Bglap genes by 3 ± 0.1 and 9.9 ± 0.6 times, relative to the control, as well as mineralization of the ECM, were observed. The volume of newly formed bone was 37.2 ± 6.2% after implantation of GAS, 20.9 ± 1.2%—non-activated Col/PRP, and 2.6 ± 1.5% in an empty defect. Conclusions: The use of Col/PRP-based matrices is an effective method for delivering of the osteoinductor gene to the site of bone tissue damage. The highest degree of healing was observed after the implantation of Col/PRP-TF/pBMP2 into the critical size defect compared to the other groups.
TGF-β Signaling in Microglia: A Key Regulator of Development, Homeostasis and Reactivity
Authors: Li Lulin , Sun Bryan , Harris Odette A. , Luo Jian
Published: October 2024

Microglia, the resident immune cells of the central nervous system (CNS), are crucial for normal brain development and function. They become reactive in response to brain injury and disease, a process known as microglial reactivity. This reactivity, along with microglial homeostasis, is tightly regulated by the local microenvironment and interactions with surrounding cells. The TGF-β signaling pathway plays an essential role in this regulation. Recent genetic studies employing microglia-specific manipulation of the TGF-β signaling pathway have shed light on its significance in microglial development, homeostasis and reactivity. This review provides an updated overview of how TGF-β signaling modulates microglial function and reactivity, contributing to our understanding of microglial biology in health and disease.
Structural Basis for Chemerin Recognition and Signaling Through Its Receptors
Authors: Liu Yezhou , Liu Aijun , Ye Richard D.
Published: October 2024

Chemerin is a chemotactic adipokine that participates in a multitude of physiological processes, including adipogenesis, leukocyte chemotaxis, and neuroinflammation. Chemerin exerts biological functions through binding to one or more of its G protein-coupled receptors (GPCRs), namely chemokine-like receptor 1 (CMKLR1), G protein-coupled receptor 1 (GPR1), and CC-motif receptor-like 2 (CCRL2). Of these receptors, CMKLR1 and GPR1 have been confirmed as signaling receptors of chemerin, whereas CCRL2 serves as a chemerin-binding protein without transmembrane signaling. High-resolution structures of two chemerin receptors are now available thanks to recent advancements in structure biology. This review focuses on the structural perspectives of the chemerin receptors with an emphasis on the structure–activity correlation, including key components of the two receptors for ligand recognition and conformational changes induced by chemerin and its derivative peptides for G protein activation. There are also comparisons between the two chemerin receptors and selected GPCRs with peptide ligands for better appreciation of the shared and distinct features of the chemerin receptors in ligand recognition and transmembrane signaling, and in the evolution of this subclass of GPCRs.
A Multicenter Physician Survey Evaluating the Use of Ki-67 in Breast Cancer Management in Canada
Authors: Leigh Jennifer , McGee Sharon F. , Vandermeer Lisa , Williams Phillip , Rushton Moira
Published: October 2024

Background: Ki-67’s response to pre-operative endocrine therapy (ET) in early breast cancer is an evidence-based tool to guide adjuvant treatment decisions. Physicians across Canada were surveyed to explore current practice patterns and perceived barriers to the use of Ki-67 in practice. Methods: Physicians were invited to participate in an anonymous survey and were eligible if they prescribed systemic therapy for breast cancer in Canada. Respondents were asked to describe their usage of Ki-67, perceptions of the evidence surrounding Ki-67 ET response, and interest in future trials using this approach. Results: The survey received 48/163 responses (29.4%). The majority of respondents (97.6%) reported access to Ki-67 testing upon request. Treatment decisions for adjuvant Abemaciclib was the most common reason (97.6%), followed by adjuvant chemotherapy decisions (16.7%). Only 19.0% had used Ki-67’s response to pre-operative ET in practice. Common barriers to this approach that were identified included a lack of awareness from other providers (54.8%), an increased resource requirement (54.8%), and a lack of timely medical oncology consultation (52.4%). The majority of physicians (85.3%) reported that they would participate in future trials using the Ki-67 endocrine response, and that rate of treatment decision change (95.2%) and cost analysis (42.3%) were important endpoints. Conclusions: Despite the widespread availability of Ki-67 testing, few physicians in Canada currently use it to assess endocrine response, predominantly due to logistical and resource constraints. There is a high level of interest in participating in future trials using this strategy, which should focus on disease related outcomes, feasibility, and the financial impact on the public healthcare system.
Early Cardiac Ischemia–Reperfusion Injury: Interactions of Autophagy with Galectin-3 and Oxidative Stress
Authors: Al-Salam Suhail , Hashmi Satwat , Jagadeesh Govindan S. , Sudhadevi Manjusha , Awwad Aktham , Nemmar Abderrahim
Published: October 2024

Background: Cardiovascular diseases are the leading cause of death worldwide, including the United Arab Emirates. Ischemia–reperfusion (IR) injury results in the death of cardiac myocytes that were viable immediately before myocardial reperfusion. We aim to investigate the role of galectin-3 (Gal-3) in autophagy during ischemia–reperfusion injuries. Methods: Male C57B6/J and Gal-3 knockout (KO) mice were used for the murine model of IR injury. Heart samples and serum were collected 24 h post-IR and were processed for immunohistochemical and immunofluorescent labeling and an enzyme-linked immunosorbent assay. Results: There was a significant increase in left ventricle (LV) concentrations of Gal-3 in Gal-3 wild-type mice compared to sham mice. There were significantly higher concentrations of LV autophagy proteins and phospho-AMPK in IR Gal-3 KO mice than in IR Gal-3 wild-type mice, compared to lower concentrations of LV phospho-mTOR and p62 in IR Gal-3 KO than in IR wild-type mice. Antioxidant activities were higher in the LVs of IR Gal-3 wild-type mice, while oxidative stress was higher in the LVs of IR Gal-3 KO mice. Conclusions: Our study supports the interaction of Gal-3 with autophagy proteins, oxidative stress, and antioxidant proteins and demonstrates that the absence of Gal-3 can enhance autophagy in the heart after IR injury.
Prognostic Significance and Treatment Response Associations of Genetic Mutations in Chronic Myelomonocytic Leukemia: A Retrospective Cohort Study
Authors: Di Jing , Yenwongfai Leonard N. , Arshad Talal , Huang Bin , McDowell Jaclyn K. , Durbin Eric B. , Munker Reinhold , Wei Sainan
Published: October 2024

Background: This retrospective cohort study investigates the prognostic significance of genetic mutations in Chronic Myelomonocytic Leukemia (CMML) and their association with treatment responses among patients treated at a single institution, juxtaposed with a statewide dataset from Kentucky. Methods: The study includes 51 patients diagnosed with CMML under the World Health Organization criteria from January 2005 to December 2023. It examines their genomic profiles and subsequent survival outcomes. The analysis also categorizes patients into CMML-1 and CMML-2 subtypes and assesses survival differences between transformed and non-transformed cases. Results: Mutations in TET2, ASXL1, and SRSF2 were found to significantly influence survival, establishing their roles as critical prognostic markers. Additionally, the cohort from the University of Kentucky exhibited distinct survival patterns compared to the broader Kentucky state population, suggesting that demographic and treatment-related factors could underlie these variances. Conclusions: This research underscores the pivotal role of targeted genetic profiling in deciphering the progression of CMML and refining therapeutic strategies. The findings emphasize the necessity for advanced genetic screening in managing CMML to better understand individual prognoses and optimize treatment efficacy, thereby offering insights that could lead to personalized treatment approaches.
Advancing Osteoarthritis Treatment: The Therapeutic Potential of Mesenchymal Stem Cell-Derived Exosomes and Biomaterial Integration
Authors: Chu Chung-Hua , Lee Ru-Ping , Wu Wen-Tien , Chen Ing-Ho , Yeh Kuang-Ting , Wang Chen-Chie
Published: October 2024

Background/Objectives: Osteoarthritis (OA) is a prevalent and debilitating joint disorder characterized by progressive cartilage degradation and inflammation, for which traditional treatments offer only symptomatic relief without halting disease progression. Exosomes, cell-free vesicles derived from mesenchymal stem cells, have emerged as a promising alternative therapy owing to their regenerative and anti-inflammatory properties. Methods: This review synthesizes findings from recent studies (2017–2023) on the therapeutic potential of exosomes in OA treatment, highlighting their ability to modulate the joint microenvironment, reduce inflammation, and promote cartilage repair by delivering bioactive molecules such as cytokines, growth factors, and regulatory ribonucleic acids. Results: We explore the integration of exosomes with biomaterials, such as hydrogels and scaffolds, to enhance their delivery and therapeutic efficacy, and we address the critical challenges associated with their clinical application, including standardization of isolation and characterization methods, scalability of production, mechanistic understanding, and long-term safety. Despite these challenges, exosome-based therapies offer several advantages over traditional and cell-based treatments, including lower immunogenicity, ease of handling, and targeted delivery of therapeutic agents to damaged tissues. Conclusions: We provide an analytical perspective on the current state of exosome research in OA, emphasizing the need for standardized production methods, deeper mechanistic insights, and rigorous long-term safety assessments. Future directions should focus on optimizing delivery systems, exploring personalized medicine approaches, and conducting comparative effectiveness studies to fully realize the potential of exosome therapies for OA treatment. Addressing these gaps will be crucial for translating exosome therapies from bench to bedside and achieving a transformative impact on OA management.
Part-Prototype Models in Medical Imaging: Applications and Current Challenges
Authors: De Santi Lisa Anita , Piparo Franco Italo , Bargagna Filippo , Santarelli Maria Filomena , Celi Simona , Positano Vincenzo
Published: October 2024

Recent developments in Artificial Intelligence have increasingly focused on explainability research. The potential of Explainable Artificial Intelligence (XAI) in producing trustworthy computer-aided diagnosis systems and its usage for knowledge discovery are gaining interest in the medical imaging (MI) community to support the diagnostic process and the discovery of image biomarkers. Most of the existing XAI applications in MI are focused on interpreting the predictions made using deep neural networks, typically including attribution techniques with saliency map approaches and other feature visualization methods. However, these are often criticized for providing incorrect and incomplete representations of the black-box models’ behaviour. This highlights the importance of proposing models intentionally designed to be self-explanatory. In particular, part-prototype (PP) models are interpretable-by-design computer vision (CV) models that base their decision process on learning and identifying representative prototypical parts from input images, and they are gaining increasing interest and results in MI applications. However, the medical field has unique characteristics that could benefit from more advanced implementations of these types of architectures. This narrative review summarizes existing PP networks, their application in MI analysis, and current challenges.
Manufacturing Anti-Reflective Subwavelength Structures on ZnS Using Femtosecond Laser Bessel Beam with Burst Mode
Authors: Wang Haoran , Li Biwen , Hu Liangbin , Zhang Fan
Published: October 2024

Increasing the transmittance of zinc sulfide (ZnS) infrared windows can effectively improve the imaging quality of infrared detection. In this study, an anti-reflective subwavelength structure (ASS) was manufactured on ZnS using a femtosecond burst Bessel laser with the goal of achieving high transmittance in the mid-infrared range. The period and depth parameters of the ASS were initially determined using the effective medium approximation (EMA) theory and subsequently optimized using the rigorous coupled-wave analysis (RCWA) method to eliminate surface Fresnel anti-reflections. The depth of the ASS increases with the number of bursts, while the structure profile transitions from Gaussian to conical. In addition, the ASS achieves 86% transmittance in the 7–10 µm range, and the average transmittance improves by 10% in the 5–12 µm range. Moreover, the wide-angle ASS with the hydrophobicity (contact angle 160°) is achieved on the ZnS window. Ultimately, the ASS on ZnS enhances the clarity of the infrared image.
Automated Surface Crack Identification of Reinforced Concrete Members Using an Improved YOLOv4-Tiny-Based Crack Detection Model
Authors: Rajesh Sofía , Jinesh Babu K. S. , Chengathir Selvi M. , Chellapandian M.
Published: October 2024

In recent times, the deployment of advanced structural health monitoring techniques has increased due to the aging infrastructural elements. This paper employed an enhanced You Only Look Once (YOLO) v4-tiny algorithm, based on the Crack Detection Model (CDM), to accurately identify and classify crack types in reinforced concrete (RC) members. YOLOv4-tiny is faster and more efficient than its predecessors, offering real-time detection with reduced computational complexity. Despite its smaller size, it maintains competitive accuracy, making it ideal for applications requiring high-speed processing on resource-limited devices. First, an extensive experimental program was conducted by testing full-scale RC members under different shear span (a) to depth ratios to achieve flexural and shear dominant failure modes. The digital images captured from the failure of RC beams were analyzed using the CDM of the YOLOv4-tiny algorithm. Results reveal the accurate identification of cracks formed along the depth of the beam at different stages of loading. Moreover, the confidence score attained for all the test samples was more than 95%, which indicates the accuracy of the developed model in capturing the types of cracks in the RC beam. The outcomes of the proposed work encourage the use of a developed CDM algorithm in real-time crack detection analysis of critical infrastructural elements.
A Calculating Method for the Height of Multi-Type Buildings Based on 3D Point Cloud
Authors: Wang Yuehuan , Yang Shuwen , Kou Ruixiong , Shi Zhuang , Li Yikun
Published: October 2024

Building height is a critical variable in urban studies, and the automated acquisition of the precise building height is essential for intelligent construction, safety, and the sustainable development of cities. The building height is often approximated by the building’s highest point. However, the calculation method of the building height of the various roof types differs according to building codes, making it challenging to accurately calculate the height of buildings with complex roof structures or multiple upper appendages. Consequently, this paper utilizes point clouds to propose an automated method for calculating building heights conforming to design codes. The model considers roof types and allows for fast, automated, and highly accurate building height estimation. First, roofs are extracted from the point cloud by combining normal vector density clustering with a region-growing algorithm. Second, combined with variational Bayes, a Gaussian mixture model is employed to segment the roof surfaces. Finally, roofs are classified based on slope characteristics, achieving the automatic acquisition of building heights for various roof types over large areas. Experiments were conducted on Vaihingen and STPLS3D datasets. In the Vaihingen area, the maximum error, root-mean-square-error (RMSE), and mean absolute error (MAE) of the measured heights are 1.92 cm, 1.18 cm, and 1.13 cm, respectively. In the STPLS3D area, these values are 1.79 cm, 0.82 cm, and 0.68 cm, respectively. The results demonstrate that the proposed method is reliable and effective, which offers valuable data for the development, construction, and planning of three-dimensional (3D) cities.