bluuebunny/crossref_metadata_2025 huggingface dataset:
App-Based Self-Adjustment—User Behavior and Adjustment Practices of Cochlear Implant Users in Everyday Life
Authors: Kliesch Sven , Chalupper Josef , Lenarz Thomas , Büchner Andreas
Published: December 2024

This study evaluated the effectiveness and usage of a smartphone application for adjusting the hearing impression of cochlear implants or hearing aids in everyday contexts. Building on previous laboratory research that demonstrated subjective auditory perception improvements through personalized settings, this research aimed to confirm these findings in real-life scenarios. Additionally, it analyzes user behavior and adaptation practices. Over a period of six months, 15 participants, including both bimodal and bilateral cochlear implant recipients, employed a self-adjustment app in their everyday lives. This application enabled them to modify the auditory experience through two distinct user interfaces and store their configurations as accessible programs. The collected data indicated that all participants were able to operate the app, and 13 of 15 participants successfully used the app throughout the whole study. In contrast to our previous findings, the acoustic environment did not affect frequency settings but did influence the choice of user interface. Bimodal users more frequently adjusted the settings for each ear independently compared to bilateral users. Most participants stated that they would also use the app outside of this study.
Speed of Reading Instructions for Creative Task Performance: Influence of Typography and Reading Media
Authors: Toure Marija , Gabrijelčič Tomc Helena , Možina Klementina
Published: December 2024

Teachers often serve as creators of written instructions that students use to complete assignments. This research investigates whether the speed at which the instructions are read is impacted by different visual designs (such as typeface shape, colour, and layout) and the media through which they are presented (digital or traditional). The objective is to determine if these factors influence reading time; therefore, an experiment was carried out. The experiment employed a 5 × 5 Latin square design, with student participants reading the same task instructions in both digital (near and far) and traditional formats. Each set of instructions was presented in a different typographic solution. Reading times were self-recorded and analysed using ANOVA to assess the effects of typographic solutions and reading media. The study did not reveal any statistically significant differences in reading speed based on the colour of the text and background as well as typographic solutions. However, it did find a statistically significant variation between reading media, with variations between digital and traditional formats. These results are crucial for enhancing the design of instructional materials, suggesting the necessity of carefully considering reading media in educational contexts.
Development and Implementation of a Deep Learning Algorithm to Evaluate the Powder Distribution Process During 3D Printing Using the LPBF Method
Authors: Korzeniowski Marcin , Małachowska Aleksandra Maria , Szymański Maciej
Published: December 2024

This article presents research work on an intelligent system that was developed to monitor and continuously evaluate the quality of metal powder distribution in the laser powder bed fusion (LPBF) 3D printing process. The 3D printer that was used to carry out the work was equipped with an industrial vision system to capture images immediately after spreading powder on the work field. The powder distribution tests showed that the most common defects were identified as an insufficiently thick layer of powder applied to the working field (super elevation), unevenly distributed powder as a result of recoater vibration (so called recoater hopping), and its wear (so called recoater streaking). In the first stage of research, a set of training data (images) was collected. Then, the implementation of the machine learning process was prepared in the Roboflow environment. After that, the learning, validation, and prediction process was carried out several times using the selected machine learning model (YOLO model implemented in a Python environment) in order to select the most effective parameters. The study showed that deep machine learning can be effectively used to identify defects in powder distribution during the laser powder bed fusion (LPBF) process.
Suppression of Strong Cultural Noise in Magnetotelluric Signals Using Particle Swarm Optimization-Optimized Variational Mode Decomposition
Authors: Shang Zhongda , Zhang Xinjun , Yan Shen , Zhang Kaiwen
Published: December 2024

To effectively separate strong cultural noise in Magnetotelluric (MT) signals under strong interference conditions and restore the true forms of apparent resistivity and phase curves, this paper proposes an improved method for suppressing strong cultural noise based on Particle Swarm Optimization (PSO) and Variational Mode Decomposition (VMD). First, the effects of two initial parameters, the decomposition scale K and penalty factor α, on the performance of variational mode decomposition are studied. Subsequently, using the PSO algorithm, the optimal combination of influential parameters in the VMD is determined. This optimal parameter set is applied to decompose electromagnetic signals, and Intrinsic Mode Functions (IMFs) are selected for signal reconstruction based on correlation coefficients, resulting in denoised electromagnetic signals. The simulation results show that, compared to traditional algorithms such as Empirical Mode Decomposition (EMD), Intrinsic Time Decomposition (ITD), and VMD, the Normalized Cross-Correlation (NCC) and signal-to-noise ratio (SNR) of the PSO-optimized VMD method for suppressing strong cultural noise increased by 0.024, 0.035, 0.019, and 2.225, 2.446, 1.964, respectively. The processing of field data confirms that this method effectively suppresses strong cultural noise in strongly interfering environments, leading to significant improvements in the apparent resistivity and phase curve data, thereby enhancing the authenticity and reliability of underground electrical structure interpretations.
Impact of Visual Kinesthetic Illusions on Reciprocal Inhibition and Motor Function
Authors: Okouchi Takeru , Hirabayashi Ryo , Sugai Nao , Yokota Hirotake , Sekine Chie , Ishigaki Tomonobu , Komiya Makoto , Sakamoto Kodai , Edama Mutsuaki
Published: December 2024

Reciprocal inhibition is often diminished in elderly individuals and those with upper motor neuron disorders. This reduction in reciprocal inhibition can hinder smooth joint movement. For subjects who have increased muscle tone and a limited range of motion in the joints, we focused on visual kinesthetic illusions as an intervention to increase reciprocal inhibition. We aimed to investigate the effects of visual kinesthetic illusions on reciprocal inhibition and motor function in the ankle joint. Participants participated in two experiments measuring reciprocal inhibition, namely reciprocal Ia inhibition and D1 inhibition, as well as motor functions related to ankle dorsiflexion and plantar flexion. Visual kinesthetic illusion was induced by displaying an image of each subject’s foot on a monitor. Our results showed that the visual kinesthetic illusion enhanced D1 inhibition and improved motor function in the ankle joint by prioritizing agonist muscle activity. We also observed a correlation between reciprocal inhibition and the muscle activity ratio. These findings suggest that visual kinesthetic illusions may improve motor function by increasing reciprocal inhibition. This study is the first to demonstrate the effects of visual kinesthetic illusion on reciprocal inhibition, and we believe that these findings can be applied in rehabilitation.
Physical Properties, Health Functionality, and Sensory Evaluation of Bread with the Unused Parts of Waxy Barley
Authors: Furuichi Tsugumi , Uno Ayane , Tsurunaga Yoko
Published: December 2024

In Japan, rising demand for waxy barley has led to concerns over bran waste. We investigated the effects of replacing wheat flour with different proportions of the waxy variety ‘Kirarimochi’ barley bran on the physical properties and health functionality of the bread. We used both the inner bran layer (IBLP) and outer bran layer (OBLP) of waxy barley as replacement sources and tested their effects on the appearance, height, specific volume, β-glucan, antioxidant properties, physical and sensory properties of bread. Bread with a 10% IBLP replacement group showed significantly increased height, specific volume, and softness compared to the control, indicating that IBLP at this level serves as an effective enhancer of bread volume and texture. At higher replacement levels (30–50% IBLP), the breads exhibited increased β-glucan content and enhanced antioxidant properties. Sensory evaluation revealed a stronger aroma, increased moistness, and stickiness of bread with 50% IBLP substitutions. OBLP was not suitable for sensory evaluation. These results show that IBLP can improve the specific volume and texture of bread and enhance its health functional components by adjusting the ratio. It also provides a clue to solving the problem of bran disposal.
Leveraging Blockchain and Consignment Contracts to Optimize Food Supply Chains Under Uncertainty
Authors: Sharma Isha , Kaur Gurpreet , Dey Bikash Koli , Majumder Arunava
Published: December 2024

The occurrence of the fourth industrial revolution (Industry 4.0) has led many industries to the path of adopting new technologies. Such technologies include blockchain, artificial intelligence (AI), and the Internet of Things (IoT). Blockchain creates the opportunity to access data and information in a decentralized manner, resulting in increased customer satisfaction. This study develops a smart newsvendor model of the food industry with consignment contracts and blockchain technology. Under a consignment policy, the central division (manufacturer) can utilize the retailer’s warehouse for storage. The producer may also have the opportunity to share the holding cost with retailers without losing the ownership of products. The main contribution of this study is to analyze the profitability of the retailing and supply chain when the blockchain technology is implemented by the food industry. Moreover, a thorough investigation of profit and loss is conducted under a consignment contract when uncertain demand is encountered. This study mainly concerns perishable food items, and increasing volatility in market demand. Two cases of probabilistic uncertainty are considered, including uniform and normal distribution. The key investigations of this study are presented in terms of (a) the effect of adopting blockchain on market demand for the food industry, (b) analysis of company profitability for perishable food items and demand uncertainty, and (c) the effect of the consignment contract under blockchain technology in the food industry. Finally, this research develops an optimization tool to numerically analyze the effect of several factors of the blockchain technology on demand. Moreover, the optimal values of the design variables and the resulting maximum profitability provide valuable insights that support industry in formulating effective policies and making informed strategic decisions.
Wavelet Analysis and the Cone of Influence: Does the Cone of Influence Impact Wavelet Analysis Results?
Authors: Kralj Lana , Hultman Martin , Lenasi Helena
Published: December 2024

Wavelet analysis (WA) decomposes laser Doppler (LD) microcirculatory signals into characteristic frequency intervals related to endothelial nitric oxide (NO)-independent, endothelial NO-dependent, neurogenic, myogenic, respiratory, and cardiac physiological influences. Since LD signals have a finite length, the WA results suffer from spectral leakage due to edge effects. The cone of influence (COI) delineates the regions of the wavelet scalogram where these effects become important. We aimed to determine whether accounting for the COI leads to significant differences in the WA results. Two typical patterns of LD signals were analysed: a baseline and a post-occlusive reactive hyperemia (PORH) signal. The WA spectra were constructed without and with excluding data affected by the COI. The relative power (RP = median power of each frequency interval/median power of the total spectrum) of the spectral components obtained without and with the COI was compared. Applying the COI correction did not significantly affect the baseline signals. On the contrary, in PORH, accounting for the COI resulted in significant differences in the RP of the endothelial NO-independent (p = 0.0005; Wilcoxon signed-rank test), endothelial NO-dependent (p = 0.0005), neurogenic (p = 0.0038), myogenic (p = 0.001), respiratory (p = 0.0002), and cardiac frequency bands (p = 0.0002). The results suggest that applying the COI correction to the WA results obtained from the LD signals is desirable, especially for transient signals.
Blockchain-Assisted Verifiable and Multi-User Fuzzy Search Encryption Scheme
Authors: Yan Xixi , Cheng Pengyu , Tang Yongli , Zhang Jing
Published: December 2024

Searchable encryption (SE) allows users to efficiently retrieve data from encrypted cloud data, but most of the existing SE solutions only support precise keyword search. Fuzzy searchable encryption agrees with practical situations well in the cloud environment, as search keywords that are misspelled to some extent can still generate search trapdoors that are as effective as correct keywords. In scenarios where multiple users can search for ciphertext, most fuzzy searchable encryption schemes ignore the security issues associated with malicious cloud services and are inflexible in multi-user scenarios. For example, in medical application scenarios where malicious cloud servers may exist, diverse types of files need to correspond to doctors in the corresponding departments, and there is a lack of fine-grained access control for sharing decryption keys for different types of files. In the application of medical cloud storage, malicious cloud servers may return incorrect ciphertext files. Since diverse types of files need to be guaranteed to be accessible by doctors in the corresponding departments, sharing decryption keys with the corresponding doctors for different types of files is an issue. To solve these problems, a verifiable fuzzy searchable encryption with blockchain-assisted multi-user scenarios is proposed. Locality-sensitive hashing and bloom filters are used to realize multi-keyword fuzzy search, and the bigram segmentation algorithm is optimized for keyword conversion to improve search accuracy. To realize fine-grained access control in multi-user scenarios, ciphertext-policy attribute-based encryption (CP-ABE) is used to distribute the shared keys. In response to the possibility of malicious servers tampering with or falsifying users’ search results, the scheme leverages the blockchain’s technical features of decentralization, non-tamperability, and traceability, and uses smart contracts as a trusted third party to carry out the search work, which not only prevents keyword-guessing attacks within the cloud server, but also solves the verification work of search results. The security analysis leads to the conclusion that the scheme is secure under the adaptively chosen-keyword attack.
IR Pulsed Laser Ablation of Carbon Materials in High Vacuum
Authors: Torrisi Lorenzo , Torrisi Alfio , Cutroneo Mariapompea
Published: December 2024

This work aimed to understand how the energy released by short laser pulses can produce different effects in carbon targets with different allotropic states. The IR pulse laser ablation, operating at 1064 nm wavelength, 3 ns pulse duration, and 100 mJ pulse energy, has been used to irradiate different types of carbon targets in a high vacuum. Graphite, highly oriented pyrolytic graphite, glassy carbon, active carbon, and vegetable carbon have exhibited different mass densities and have been laser irradiated. Time-of-flight (TOF) measurements have permitted the evince of the maximum carbon ion acceleration in the generated plasma (of about 200 eV per charge state) and the maximum yield emission (96 μg/pulse in the case of vegetal carbon) along the direction normal to the irradiated surface. The ion energy analyzer measured the carbon charge states (four) and their energy distributions. Further plasma investigations have been performed using a fast CCD camera image and surface profiles of the generated craters to calculate the angular emission and the ablation yield for each type of target. The effects as a function of the target carbon density and binding energy have been highlighted. Possible applications for the generation of thin films and carbon nanoparticles are discussed.
Community Detection Framework Using Deep Learning in Social Media Analysis
Authors: Shen Ao , Chow Kam-Pui
Published: December 2024

Social media analysis aims to collect and analyze social media user information and communication content. When people communicate through messages, phone calls, emails, and social media platforms, they leave various records on their devices and the Internet, forming a huge social network. Community detection can help investigators analyze group leaders and community structure, which is significant to further crime control, identifying coordinated campaigns, and analyzing social network dynamics. This paper proposes the application of deep learning methods for community detection. Our main idea is to utilize social network topology and social network communication content to construct user features. The proposed end-to-end community detection framework is the implementation of Graph Convolution Network and can display the social network topology, locate the core members of the community, and show the connections between users. We evaluate our framework on the Enron email dataset. Experimental results indicate that our proposed model achieves a 1.1% higher modularity score than the unsupervised benchmark methods. We also concluded that the community detection framework should be able to analyze social networks, enabling investigators to reveal connections between people.
Redefining Urbanism in Perspective of Climate Change: Floating Cities Concept
Authors: Januszkiewicz Krystyna , Gołębiewski Jakub , Czarnecki Bartosz , Turecki Adam
Published: December 2024

This article analyzes the concept of floating cities in the context of increasing threats resulting from climate change. It explores the potential of a floating city concept to provide sustainable and livable conditions on a large scale in response to the growing climate crisis. Specifically, this article considers whether climate change is prompting a redefinition of urbanism and examines how the floating city concept can be useful from this perspective. The analysis draws on ideas related to megastructures, particularly those based on platforms. A pioneer in this field was Kiyonori Kikutake, who in 1958–1963 presented three concepts of floating cities under the name Marine City. His designs were centered around modularity and mobility. Today, Kikutake’s vision is experiencing a resurgence as climate change forces architects and urban planners to rethink traditional cities. Contemporary architects such as Vincent Callebaut and Bjarke Ingels are now gaining attention for their innovative designs of floating cities, which are being closely examined by experts and policymakers. The first part of this article provides a comparative analysis of Marine City with contemporary examples of megastructures, such as the Lilypad and Oceanix projects, illustrating how the concept of floating cities have evolved over the centuries. The question is, which solutions developed by Japanese Metabolists remain relevant and how has modern technology enriched and advanced the concept of living on water? The second part of the article analyzes the potential of floating cities to redefine urbanism in response to the growing threat of climate change. This analysis primarily focuses on the possible interactions between floating cities and the environment. The results show that the challenges posed by climate change are redefining the urban planning paradigms formed in the first half of the 20th century. The floating city concept shows some potential as a viable response to these challenges.
Two-Electron Atomic Systems—A Simple Method for Calculating the Ground State near the Nucleus: Some Applications
Authors: Liverts Evgeny Z. , Krivec Rajmund
Published: December 2024

A simple method of non-relativistic variational calculations of the electronic structure of a two-electron atom/ion, primarily near the nucleus, is proposed. The method as a whole consists of a standard solution of a generalized matrix eigenvalue equation, all matrix elements of which are reduced to a numerical calculation of one-dimensional integrals. The distinctive features of the method are as follows: The use of the hyperspherical coordinate system. The inclusion of logarithms of the hyperspherical radius R in the basis functions, similar to the Fock expansion. Using a special basis function including the leading angular Fock coefficients to provide the correct behavior of the wave function near the nucleus. The main numerical parameters characterizing the properties of the helium atom and a number of helium-like ions near the nucleus are calculated and presented in tables. Among others, the specific coefficients, a21, of the Fock expansion, which can only be calculated using a wave function with the correct behavior near the nucleus, are presented in table and graphs.
State-Selective Double Photoionization of Atomic Carbon and Neon
Authors: Yip Frank L.
Published: December 2024

Double photoionization (DPI) allows for a sensitive and direct probe of electron correlation, which governs the structure of all matter. For atoms, much of the work in theory and experiment that informs our fullest understanding of this process has been conducted on helium, and efforts continue to explore many-electron targets with the same level of detail to understand the angular distributions of the ejected electrons in full dimensionality. Expanding on previous results, we consider here the double photoionization of two 2p valence electrons of atomic carbon and neon and explore the possible continuum states that are connected by dipole selection rules to the coupling of the outgoing electrons in 3P, 1D, and 1S initial states of the target atoms. Carbon and neon share these possible symmetries for the coupling of their valence electrons. Results are presented for the energy-sharing single differential cross section (SDCS) and triple differential cross section (TDCS), further elucidating the impact of the initial state symmetry in determining the angular distributions that are impacted by the correlation that drives the DPI process.
Gas Emissions from Lithium-Ion Batteries: A Review of Experimental Results and Methodologies
Authors: Nilsson Elna J. K. , Ahlberg Tidblad Annika
Published: December 2024

Gas emissions from lithium-ion batteries (LIBs) have been analysed in a large number of experimental studies over the last decade, including investigations of their dependence on the state of charge, cathode chemistry, cell capacity, and many more factors. Unfortunately, the reported data are inconsistent between studies, which can be explained by weaknesses in experimental methodologies, the misinterpretation of data, or simply due to the comparison of datasets that build on different prerequisites. In the present work, the literature on gassing from battery components and battery cells is reported, with a focus on vent gas composition resulting from internal chemical processing in the battery and excluding studies where the gases are combusted after venting. The aim is to identify datasets of high quality that contribute to the advancement of our understanding of gas emissions from LIBs. Gas compositions from different stages in the gassing process are included, starting with the slow formation of gases during normal operation via mild thermal events to a thermal runaway (TR) with extensive gas production. Available published data are used to map gas quantity and composition from LIBs undergoing venting, with or without a TR, and to identify gaps in understanding and the need for further research.
Experimental Investigation of the Mechanical and Electrical Failure of the Electrode Tab of Lithium-Ion Pouch Cells Under Quasi-Static Mechanical Load
Authors: Höschele Patrick , Heindl Simon Franz , Ellersdorfer Christian
Published: December 2024

The electrode tabs of pouch cells are rigidly joined to the bus bar in a battery module to achieve an electric connection. The effect of abusive mechanical loads arising from crash-related deformation or the possible movement of battery cells caused by operation-dependent thickness variations has so far never been investigated. Three quasi-static abuse tests for the anode and cathode electrode tabs were conducted with pouch cells at 100% SOC. Tensile tests on the anode, cathode and pouch foil were performed in order to explain differences between the anode and cathode in the abuse tests. The experiments revealed different failure mechanisms for the anode and cathode electrode tabs. The cathode failed at an average maximum load of 940.3 N through an external rupture of the electrode tab. The anode failed at an average maximum load of 868.9 N through a rupture of the single electrode sheets and the opening of the pouch foil. No thermal runaway occurred for either cathode or anode. The results of this study reveal a more critical failure behavior for the anode electrode tab, which can be addressed in the future by adding a predetermined breaking point and adapting the geometry of the anode electrode tab.
Li Chemical and Tracer Diffusivities in LiCoO2 Sintered Pellets
Authors: Hüger Erwin , Schmidt Harald
Published: December 2024

LiCoO2 (LCO) is a crucial active material for positive electrodes of commercial lithium-ion batteries. It is typically present in the form of micrometer-sized LCO particles, which are surrounded by binders and conductive agents with a thickness of tens of microns. In order to determine the intrinsic Li transport parameters of pure crystalline LCO, it is necessary to measure the Li diffusivity at room temperature in sintered LCO pellets free of additives. The LCO sintered bulk material consists of interconnected, about 3 µm clusters, composed of grains of about 70 nanometers in size. The Li chemical and tracer diffusivities are determined using electrochemical impedance spectroscopy (EIS) and potentiostatic intermittent titration technique (PITT), while the latter ones are in the range between 10−9 and 10−28 m2s−1, depending on the application of different relevant formulas and characteristic parameters. Consequently, it is essential to apply a classical non-electrochemical and Li selective method of tracer diffusion determination like 6Li depth profiling and secondary ion mass spectrometry (SIMS) for comparison. Li tracer diffusivities of about 10−22 m2s−1 at room temperature are obtained by the extrapolation of the SIMS results from higher temperatures. This significantly narrows the range of reliable electrochemically determined Li tracer diffusivities to a more limited range, between 10−21 and 10−22 m2s−1.
Temporal Tissue Remodeling in Volumetric Muscle Injury with Endothelial Cell-Laden Patterned Nanofibrillar Constructs
Authors: Habing Krista M. , Alcazar Cynthia A. , Dobson Nathaniel , Tan Yong How , Huang Ngan F. , Nakayama Karina H.
Published: December 2024

A primary challenge following severe musculoskeletal trauma is incomplete muscle regeneration. Current therapies often fail to heal damaged muscle due to dysregulated healing programs and insufficient revascularization early in the repair process. There is a limited understanding of the temporal changes that occur during the early stages of muscle remodeling in response to engineered therapies. Previous work demonstrated that nanotopographically patterned scaffolds provide cytoskeletal guidance and direct endothelial angiogenic and anti-inflammatory phenotypes. The aim of this study was to evaluate how endothelial cell (EC) patterning guides temporal and histomorphological muscle remodeling after muscle injury. In the current study, mice were treated with EC-laden engineered constructs that exhibited either aligned or random patterning of collagen nanofibrils, following a volumetric muscle loss injury (VML). Remodeling was evaluated at 2, 7, and 21 days post injury. Over the 21-day study, all groups (Acellular Aligned, EC Aligned, EC Random) demonstrated similar significant increases in vascular density and myogenesis. Animals treated with acellular controls demonstrated a two-fold decrease in muscle cross-sectional area between days 2 and 21 post injury, consistent with VML-induced muscle atrophy; however, animals treated with patterned EC-laden constructs exhibited preservation of muscle mass. The implantation of an EC-laden construct led to a 50% increase in the number of animals exhibiting areas of fibrous remodeling adjacent to the construct, along with greater collagen deposition (p < 0.01) compared to acellular controls 21 days post injury. These findings suggest that nanotopographically patterned EC-laden constructs may guide early muscle-protective programs that support muscle mass retention through myo-vascular independent pathways.
AutoML-Driven Insights into Patient Outcomes and Emergency Care During Romania’s First Wave of COVID-19
Authors: Simon Sonja C. S. , Bibi Igor , Schaffert Daniel , Benecke Johannes , Martin Niklas , Leipe Jan , Vladescu Cristian , Olsavszky Victor
Published: December 2024

Background: The COVID-19 pandemic severely impacted healthcare systems, affecting patient outcomes and resource allocation. This study applied automated machine learning (AutoML) to analyze key health outputs, such as discharge conditions, mortality, and COVID-19 cases, with the goal of improving responses to future crises. Methods: AutoML was used to train and validate models on an ICD-10 dataset covering the first wave of COVID-19 in Romania (January–September 2020). Results: For discharge outcomes, Light Gradient Boosted models achieved an F1 score of 0.9644, while for mortality 0.7545 was reached. A Generalized Linear Model blender achieved an F1 score of 0.9884 for “acute or emergency” cases, and an average blender reached 0.923 for COVID-19 cases. Older age, specific hospitals, and oncology wards were less associated with improved recovery rates, while mortality was linked to abnormal lab results and cardiovascular/respiratory diseases. Patients admitted without referral, or patients in hospitals in the central region and the capital region of Romania were more likely to be acute cases. Finally, counties such as Argeş (South-Muntenia) and Brașov (Center) showed higher COVID-19 infection rates regardless of age. Conclusions: AutoML provided valuable insights into patient outcomes, highlighting variations in care and the need for targeted health strategies for both COVID-19 and other health challenges.
Adenoviral Vectors for Gene Therapy of Hereditary Diseases
Authors: Muravyeva Anna , Smirnikhina Svetlana
Published: December 2024

Adenoviral vectors (AdVs) are effective vectors for gene therapy due to their broad tropism, high capacity, and high transduction efficiency, which makes them actively used as oncolytic vectors and for creating vector vaccines. However, despite their numerous advantages, AdVs have not yet found their place in gene therapy for hereditary diseases. This review provides an overview of AdVs, their features, and clinical trials using them for gene replacement therapy in monogenic diseases and analyzes the reasons for the failures of these studies. Additionally, current research on the modification of AdVs to reduce immune responses and target delivery is discussed.
Regulation of Vascular Injury and Repair by P21-Activated Kinase 1 and P21-Activated Kinase 2: Therapeutic Potential and Challenges
Authors: Han Chuting , Zhu Mengying , Liu Yiting , Yang Yan , Cheng Jun , Li Pengyun
Published: December 2024

The PAK (p21-activated kinases) family is a class of intracellular signal transduction protein kinases that regulate various cellular functions, mainly through their interactions with small GTP enzymes. PAK1 and PAK2 in the PAK kinase family are key signal transduction molecules that play important roles in various biological processes, including morphological changes, migration, proliferation, and apoptosis, and are involved in the progression of many diseases. Abnormal expression or dysregulation of PAK1 and PAK2 may be associated with several diseases, including cancer, neurological diseases, etc. The current research mainly focuses on studying the role of PAK and PAK inhibitors in the regulation of cancer progression, but relatively few reports are available that explore their potential role in cardiovascular diseases. Vascular injury and repair are complex processes involved in many cardiovascular conditions, including atherosclerosis, restenosis, and hypertension. Emerging research suggests that PAK1 and PAK2 have pivotal roles in vascular endothelial cell functions, including migration, proliferation, and angiogenesis. These kinases also modulate vascular smooth muscle relaxation, vascular permeability, and structural alterations, which are critical in the development of atherosclerosis and vascular inflammation. By targeting these activities, PAK proteins are essential for both normal vascular physiology and the pathogenesis of vascular diseases, highlighting their potential as therapeutic targets for vascular health. This review focuses on recent studies that offer experimental insights into the mechanisms by which PAK1 and PAK2 regulate the biological processes of vascular injury and repair and the therapeutic potential of the current existing PAK inhibitors in vascular-related diseases. The limitations of treatment with some PAK inhibitors and the ways that future development can overcome these challenges are also discussed.
Orally Administered Lactobacilli Strains Modulate Alveolar Macrophages and Improve Protection Against Respiratory Superinfection
Authors: Albarracin Leonardo , Dentice Maidana Stefania , Fukuyama Kohtaro , Elean Mariano , Argañaraz Aybar Julio Nicolás , Suda Yoshihito , Nishiyama Keita , Kitazawa Haruki , Villena Julio
Published: December 2024

Orally administered immunomodulatory lactobacilli can stimulate respiratory immunity and enhance the resistance to primary infections with bacterial and viral pathogens. However, the potential beneficial effects of immunomodulatory lactobacilli against respiratory superinfection have not been evaluated. In this work, we showed that the feeding of infant mice with Lacticaseibacillus rhamnosus CRL1505 or Lactiplantibacillus plantarum MPL16 strains can reduce susceptibility to the secondary pneumococcal infection produced after the activation of TLR3 in the respiratory tract or after infection with RVS. The treatment of mice with CRL1505 or MPL16 strains by the oral route improved the production of interferons in the respiratory tract, differentially modulated the balance of pro- and anti-inflammatory cytokines, reduced bacterial replication, and diminished lung damage. Additionally, we demonstrated that orally administered lactobacilli confer longstanding protection against secondary Streptococcus pneumoniae infection and that this effect would be mediated by the stimulation of trained alveolar macrophages. This work contributes to revealing the mechanisms involved in the modulation of the gut–lung axis by beneficial microbes by demonstrating that specific lactobacilli strains, through the stimulation of the common mucosal immune system, would be able to support the development of trained alveolar macrophages that would confer longstanding protection against secondary bacterial challenges produced after a primary inflammatory event in the respiratory mucosa.
Determination of Free Fatty Acids in Breast Milk Reveals the Presence of Hydroxypalmitic and Stearic Acids
Authors: Kokotou Maroula G.
Published: December 2024

Breast milk is a rich source of fatty acids (FAs) while being irreplaceable for the health and development of an infant. Herein, we present a fast and simple method for the direct detection and quantification of 37 free FAs (FFAs) in breast milk samples, avoiding any derivatization step, and a study on the % variation of FA contents in samples collected from the same mother within five consecutive days. The average breakdown of FAs was 60.5% saturated and 39.5% unsaturated, in which polyunsaturated FAs were 13.3% and monounsaturated FAs 26.2%. The most abundant FFA in the breast milk samples was C12:0 (18.3%), followed by C10:0 (15.0%), suggesting that further attention must be paid to the presence and role of medium-chain FAs. Among unsaturated FAs, oleic acid (C18:1 n-9) (13.3%) and linoleic acid (C18:2 n-6) (10.1%) were the most abundant. Remarkable variations of FFA contents within the five consecutive days were observed for C8:0, C10:0, C12:0, C18:1 n-9, and C18:2 n-6. The two isomers α-linolenic acid (C18:3 n-3) and γ-linolenic acid (C18:3 n-6) were quantified in all breast milk samples. The ratio of γ-linolenic acid, which most recently is important for cardiac metabolic maturation, to α-linolenic acid was found to be 1:2. Most importantly, in the present study, we explored the presence of bioactive saturated monohydroxy fatty acids (SHFAs), demonstrating for the first time the existence of distinct hydroxypalmitic and hydroxystearic acids (HPAs and HSAs, respectively) in breast milk.
Angiogenesis Dynamics: A Computational Model of Intravascular Flow Within a Structural Adaptive Vascular Network
Authors: Nivlouei Sahar Jafari , Guerra Ana , Belinha Jorge , Mangir Naside , MacNeil Sheila , Salgado Christiane , Monteiro Fernando Jorge , Natal Jorge Renato
Published: December 2024

Background: Understanding vascular development and the key factors involved in regulating angiogenesis—the growth of new blood vessels from pre-existing vasculature—is crucial for developing therapeutic approaches to promote wound healing. Computational techniques offer valuable insights into improving angiogenic strategies, leading to enhanced tissue regeneration and improved outcomes for chronic wound healing. While chorioallantoic membrane (CAM) models are widely used for examining fundamental mechanisms in vascular development, they lack quantification of essential parameters such as blood flow rate, intravascular pressure, and changes in vessel diameter. Methods: To address this limitation, the current study develops a novel two-dimensional mathematical model of angiogenesis, integrating discrete and continuous modelling approaches to capture intricate cellular interactions and provide detailed information about the capillary network’s structure. The proposed hybrid meshless-based model simulates sprouting angiogenesis using the in vivo CAM system. Results: The model successfully predicts the branching process with a total capillary volume fraction deviation of less than 15% compared to experimental data. Additionally, it implements blood flow through the capillary network and calculates the distribution of intravascular pressure and vessel wall shear stress. An adaptive network is introduced to consider capillary responses to hemodynamic and metabolic stimuli, reporting structural diameter changes across the generated vasculature network. The model demonstrates its robustness by verifying numerical outcomes, revealing statistically significant differences with deviations in key parameters, including diameter, wall shear stress (p < 0.05), circumferential wall stress, and metabolic stimuli (p < 0.01). Conclusion: With its strong predictive capability in simulating intravascular flow and its ability to provide both quantitative and qualitative assessments, this research enhances our understanding of angiogenesis by introducing a biologically relevant network that addresses the functional demands of the tissue.
Extracellular Vesicles from Mesenchymal Stem Cells: Potential as Therapeutics in Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD)
Authors: Zou Xue , Brigstock David
Published: December 2024

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by the accumulation of triglycerides within hepatocytes, which can progress to more severe conditions, such as metabolic dysfunction-associated steatohepatitis (MASH), which may include progressive fibrosis, leading to cirrhosis, cancer, and death. This goal of this review is to highlight recent research showing the potential of mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) in reducing the key pathogenic pathways of MASLD or MASH. Methods: Relevant published studies were identified using PubMed with one or more of the following search terms: MASLD, MASH, NAFLD, NASH, exosome, extracellular vesicle (EV), therapy, and/or mesenchymal stem cells (MSC). The primary literature were subsequently downloaded and summarized. Results: Using in vitro or in vivo models, MSC-EVs have been found to counteract oxidative stress, a significant contributor to liver injury in MASH, and to suppress disease progression, including steatosis, inflammation, and, in a few instances, fibrosis. Some of these outcomes have been attributed to specific EV cargo components including microRNAs and proteins. Thus, MSC-EVs enriched with these types of molecules may have improved the therapeutic efficacy for MASLD/MASH and represent a novel approach to potentially halt or reverse the disease process. Conclusions: MSC-EVs are attractive therapeutic agents for treating MASLD/MASH. Further studies are necessary to validate the clinical applicability and efficacy of MSC-EVs in human MASH patients, focusing on optimizing delivery strategies and identifying the pathogenic pathways that are targeted by specific EV components.
TRAP-Induced Platelet Reactivity Is Inhibited by Omega-3 Fatty Acid-Derived Prostaglandin E3 (PGE3)
Authors: Osete José-Miguel , García-Candel Faustino , Fernández-Gómez Francisco-José , Blanquer Miguel , Atucha Noemí M. , García-Estañ Joaquín , Iyú David
Published: December 2024

Background: Prostaglandins are naturally occurring local mediators that can participate in the modulation of the cardiovascular system through their interaction with Gs/Gi-coupled receptors in different tissues and cells, including platelets. Thrombin is one of the most important factors that regulates platelet reactivity and coagulation. Clinical trials have consistently shown that omega-3 fatty acid supplementation lowers the risk for cardiovascular mortality and morbidity. Since omega-3 fatty acids are the main precursors of PGE3 in vivo, it would be relevant to investigate the effects of PGE3 on Thrombin Receptor Activating Peptide (TRAP-6)-induced platelet reactivity to determine the receptors and possible mechanisms of action of these compounds. Methods: We have measured platelet aggregation, P-selectin expression, and vasodilator-stimulated phosphoprotein (VASP) phosphorylation to evaluate platelet reactivity induced by TRAP-6 to determine the effects of PGE3 on platelet function. Results: We assessed the ability of DG-041, a selective prostanoid EP3 receptor antagonist, and of ONO-AE3-208, a selective prostanoid EP4 receptor antagonist, to modify the effects of PGE3. PGE3 inhibited TRAP-6-induced platelet aggregation and activation. This inhibition was enhanced in the presence of a Gi-coupled EP3 receptor antagonist and abolished in the presence of a Gs-coupled EP4 receptor antagonist. The effects of PGE3 were directly related to changes in cAMP, assessed by VASP phosphorylation. Conclusions: The general effects of PGE3 on human platelet reactivity are the consequence of a balance between activatory and inhibitory effects at receptors that have contrary effects on adenylate cyclase. These results indicate a potential mechanism by which omega-3 fatty acids underlie cardioprotective effects.
Evaluating Feature Selection Methods for Accurate Diagnosis of Diabetic Kidney Disease
Authors: Maeda-Gutiérrez Valeria , Galván-Tejada Carlos E. , Galván-Tejada Jorge I. , Cruz Miguel , Celaya-Padilla José M. , Gamboa-Rosales Hamurabi , García-Hernández Alejandra , Luna-García Huizilopoztli , Villalba-Condori Klinge Orlando
Published: December 2024

Background/Objectives: The increase in patients with type 2 diabetes, coupled with the development of complications caused by the same disease is an alarming aspect for the health sector. One of the main complications of diabetes is nephropathy, which is also the main cause of kidney failure. Once diagnosed, in Mexican patients the kidney damage is already highly compromised, which is why acting preventively is extremely important. The aim of this research is to compare distinct methodologies of feature selection to identify discriminant risk factors that may be beneficial for early treatment, and prevention. Methods: This study focused on evaluating a Mexican dataset collected from 22 patients containing 32 attributes. To reduce the dimensionality and choose the most important variables, four feature selection algorithms: Univariate, Boruta, Galgo, and Elastic net were implemented. After selecting suitable features detected by the methodologies, they are included in the random forest classifier, obtaining four models. Results: Galgo with Random Forest achieved the best performance with only three predictors, “creatinine”, “urea”, and “lipids treatment”. The model displayed a moderate classification performance with an area under the curve of 0.80 (±0.3535 SD), a sensitivity of 0.909, and specificity of 0.818. Conclusions: It is demonstrated that the proposed methodology has the potential to facilitate the prompt identification of nephropathy and non-nephropathy patients, and thereby could be used in the clinical area as a preliminary computer-aided diagnosis tool.
Chemerin and Polycystic Ovary Syndrome: A Comprehensive Review of Its Role as a Biomarker and Therapeutic Target
Authors: Palomba Stefano , Seminara Giuseppe , Costanzi Flavia , Caserta Donatella , Aversa Antonio
Published: December 2024

Background: Chemerin, an adipokine implicated in inflammatory, metabolic, and adipogenic processes, has been detected in high serum concentration in women with polycystic ovary syndrome (PCOS) and seems to play a role in PCOS pathogenesis. Moreover, at present, no comprehensive and critical document is available in the literature on this topic. The aim of the current study was to comprehensively review the latest available data to confirm the evidence about the association between chemerin and PCOS, highlighting its potential role as an upcoming biomarker and therapeutic target. Methods: A search in the literature of studies published between 2019 and 2024 was conducted using PubMed, Cochrane Library, and Web of Science, focusing on research related to chemerin, PCOS, and PCOS-related features, comorbidities, and complications. A qualitative structured synthesis of key findings was performed according to the specific thematic areas selected, including and discussing clinical data on women with PCOS and experimental studies in humans and animal models of PCOS. Results: Available data confirm increased serum levels of chemerin in women with PCOS compared with controls, independent of obesity and body mass index. Chemerin is associated with insulin resistance, hyperandrogenism, and ovarian dysfunction in PCOS individuals, inhibiting folliculogenesis and steroidogenesis. Experimental animal models underscore chemerin’s regulatory roles through its receptors within the hypothalamic–pituitary–ovarian axis and peripheral tissues. High systemic levels of chemerin in PCOS may also be related to the increased risk of pregnancy complications, especially gestational diabetes mellitus and preeclampsia. Conclusions: The current review study highlights the role of chemerin in PCOS pathophysiology, severity, and associated comorbidities and complications, assessing its value as a future biomarker and foreshadowing its potential as a therapeutic target.