bluuebunny/crossref_metadata_2025 huggingface dataset:
Nanoencapsulation of Maqui (Aristotelia chilensis) Extract in Chitosan–Tripolyphosphate and Chenopodin-Based Systems
Authors: Andrade Daniela , Maldonado-Bravo Francisca , Alburquerque Amador , Pérez Camilo , Gamboa Alexander , Caro Nelson , Díaz-Dosque Mario , Gotelland Martin , Abugoch Lilian , Tapia Cristian
Published: February 2024

Maqui berries contain a high percentage of anthocyanins with high antioxidant and anti-inflammatory capacity but that are unstable in the colonic site. Nanocarriers based on polysaccharides and/or proteins can protect against the degradation of anthocyanins. The aim of this study was the nanoencapsulation of maqui extract (ME) in chitosan–tripolyphosphate (CTPP-ME), chenopodin (CH-ME), and chenopodin–alginate (CHA-ME). A standardised ME was prepared and then encapsulated in the nanosystems. The physicochemical properties, encapsulation parameters, and the interactions of ME with the nanovehicles were characterised. The cyanidin-3-glucoside released and ORAC activity in phosphate buffer at pH 7.4 were evaluated. The content of ME was 8–9 mg of cyanidin-3-glucoside/g of extract. CTPP with ME at 3% obtained the highest encapsulation efficiency (EE = 91%), and no significant differences were observed in size (274–362 nm), PDI (0.5–0.7), and zeta potential (+34–+41 mV) when the concentration of ME changed from 1% to 5%. CH-ME was shown to be smaller (152 nm) than CTPP-ME, and CH-ME and CHA-ME showed lower EE (79% and 54%, respectively) than CTPP-ME. FT-IR revealed a stronger interaction of ME with CTPP-ME than with CH-ME. Both systems showed a significantly lower release than free ME, and the T50 value of CTPP-ME 3% (328 min) was higher than CH-ME (197 min). Both protected the ORAC activity of ME.
A Novel Plant-Based Nutraceutical Combined with Exercise Can Revert Oxidative Status in Plasma and Liver in a Diet-Induced-Obesity Animal Model
Authors: Guzmán-Carrasco Ana , Kapravelou Garyfallia , López-Jurado María , Bermúdez Francisco , Andrés-León Eduardo , Terrón-Camero Laura C. , Prados José , Melguizo Consolación , Porres Jesus M. , Martínez Rosario
Published: February 2024

The prevalence of obesity increases alarmingly every year mostly due to external factors such as high-fat and high-refined sugar intake associated with a sedentary lifestyle. It triggers metabolic disorders such as insulin resistance, hyperlipemia, non-alcoholic fatty liver disease, chronic inflammation, oxidative stress, and gut microbiota dysbiosis. The aim of this study was to evaluate the beneficial effects of a combined intervention with caloric restriction, nutraceutical intake, and a mixed training protocol on oxidative stress, inflammation, and gut dysbiosis derived from the development of obesity in a C57BL6/J mouse experimental model of diet-induced obesity (4.6 Kcal/g diet, 45% Kcal as fat, and 20% fructose in the drinking fluid). The nutraceutical was formulated with ethanolic extracts of Argania spinosa pulp (10%) and Camelina sativa seeds (10%) and with protein hydrolysates from Psoralea corylifolia seeds (40%) and Spirodela polyrhiza whole plants (40%). The combination of nutraceutical and exercise decreased the animals’ body weights and inflammatory markers (TNFα, IL-6, and resistin) in plasma, while increasing gene expression of cat, sod2, gsta2, and nqo1 in the liver. Obese animals showed lower β-diversity of microbiota and a higher Firmicutes/Bacteroidetes ratio vs. normocaloric controls that were reversed by all interventions implemented. Dietary inclusion of a nutraceutical with high antioxidant potential combined with an exercise protocol can be beneficial for bodyweight control and improvement of metabolic status in patients undergoing obesity treatment.
Comparative Study of Droplet Diameter Distribution: Insights from Experimental Imaging and Computational Fluid Dynamics Simulations
Authors: Vhora Kasimhussen , Janiga Gábor , Lorenz Heike , Seidel-Morgenstern Andreas , Gutierrez Maria F. , Schulze Peter
Published: February 2024

The interfacial area between two phases plays a crucial role in the mass transfer rate of gas–liquid processes such as absorption. In this context, the droplet size distribution within the flow field of a droplet-based absorber significantly affects the surface area, thereby influencing the absorption efficiency. This study focuses on developing a computational fluid dynamics (CFD) model to predict the size and distribution of water droplets free-falling in a transparent square tube. This model serves as a digital twin of our experimental setup, enabling a comparative analysis of experimental and computational results. For the accurate measurement of droplet size and distribution, specialized experimental equipment was developed, and a high-speed camera along with Fiji software was used for the capturing and processing of droplet images. At the point of injection and at two different heights, the sizes and distributions of falling droplets were measured using this setup. The interaction between the liquid water droplets and the gas phase within the square tube was modeled using the Eulerian–Lagrangian (E-L) framework in the STAR-CCM+ software. The E-L multiphase CFD model yielded approximations with errors ranging from 11 to 27% for various average mean diameters, including d10, d20, d30, and d32, of the liquid droplets at two distinct heights (200 mm and 400 mm) for both nozzle plates. This comprehensive approach provides valuable insights into the dynamics of droplet-based absorption processes.
Measurement of Regional Electric Vehicle Adoption Using Multiagent Deep Reinforcement Learning
Authors: Choi Seung Jun , Jiao Junfeng
Published: February 2024

This study explores the socioeconomic disparities observed in the early adoption of Electric Vehicles (EVs) in the United States. A multiagent deep reinforcement learning-based policy simulator was developed to address the disparities. The model, tested using data from Austin, Texas, indicates that neighborhoods with higher incomes and a predominantly White demographic are leading in EV adoption. To help low-income communities keep pace, we introduced tiered subsidies and incrementally increased their amounts. In our environment, with the reward and policy design implemented, the adoption gap began to narrow when the incentive was equivalent to an increase in promotion from 20% to 30%. Our study’s framework provides a new means for testing policy scenarios to promote equitable EV adoption. We encourage future studies to extend our foundational study by adding specifications.
SysML4GDPSim: A SysML Profile for Modeling Geometric Deviation Propagation in Multistage Manufacturing Systems Simulation
Authors: Benavent-Nácher Sergio , Rosado Castellano Pedro , Romero Subirón Fernando
Published: February 2024

In recent years, paradigms like production quality or zero-defect manufacturing have emerged, highlighting the need to improve quality and reduce waste in manufacturing systems. Although quality can be analyzed from various points of view during different stages of a manufacturing system’s lifecycle, this research focuses on a multidomain simulation model definition oriented toward the analysis of productivity and geometric quality during early design stages. To avoid inconsistencies, the authors explored the definition of descriptive models using system modeling language (SysML) profiles that capture domain-specific semantics defining object constraint language (OCL) rules, facilitating the assurance of model completeness and consistency regarding this specific knowledge. This paper presents a SysML profile for the simulation of geometric deviation propagation in multistage manufacturing systems (SysML4GDPSim), containing the concepts for the analysis of two data flows: (a) coupled discrete behavior simulation characteristic of manufacturing systems defined using discrete events simulation (DEVS) formalism; and (b) geometric deviation propagation through the system based on the geometrical modeling of artifacts using concepts from the topologically and technologically related surfaces (TTRS) theory. Consistency checking for this type of multidomain simulation model and the adoption of TTRS for the mathematical analysis of geometric deviations are the main contributions of this work, oriented towards facilitating the collaboration between design and analysis experts in the manufacturing domain. Finally, a case study shows the application of the proposed profile for the simulation model of an assembling line, including the model’s transformation to Modelica and some experimental results of this type of analysis.
Acoustic Requalification of an Urban Evolving Site and Design of a Noise Barrier: A Case Study at the Bologna Engineering School
Authors: Fusaro Gioia , Garai Massimo
Published: February 2024

The increase in new infrastructure development has raised closer attention to the environmental noise of new expansion areas. This study investigates the urban evolution of Terracini Street’s surrounding area in the Navile district, Bologna, Italy. In the last 20 years, this area has undergone various transformations, from a suburban industrial area to a new university and residential one. First, the morphologic and infrastructural characteristics of the site are established. Then, the existing regulations (acoustic, urban, and infrastructural regulations, whether local or national) are evaluated. Next, the results of environmental noise measurements are presented. Since a heavily trafficked infrastructure is very close to the occupied public area, noise limits are severely exceeded. A noise mitigation design stage follows, focusing on a novel noise barrier design. Specifically, particular attention is paid to the visual and ecological impact of the noise barrier on the area’s landscape, which must be representative of the new location of the School of Engineering. The sonic crystal technique is exploited to implement an effective noise barrier (average insertion loss of 10 dB(A) in the 200 Hz–1 kHz range), allowing air ventilation and visual transparency. This case study could further evolve using other acoustic metamaterial techniques or in different application sites.
The Role of Geological Methods in the Prevention and Control of Urban Flood Disaster Risk: A Case Study of Zhengzhou
Authors: Wang Shuaiwei , Sun Weichao , Wang Xiuyan , Sun Lin , Liu Songbo
Published: February 2024

The frequent occurrence of urban flood disasters is a major and persistent problem threatening the safety of cities in China and elsewhere in the world. As this issue is so pervasive, exploring new methods for more effective risk prevention and urban flood disaster control is now being prioritized. Taking the case of the city of Zhengzhou as an example, this paper proposes using geological, hydrogeological, ecological, and environmental conditions together with appropriate engineering designs to address the problem of urban flooding. The strategy includes integrating urban sponge–hydrogeological conditions, ecological engineering, and the construction of deep underground water storage facilities. Field investigations, data collection and analysis, in situ observations, testing, and laboratory experiments, are analyzed to explain the formation mechanism and means to mitigate flood disasters in Zhengzhou. Our results suggest that the appropriate use of geological, ecological, and hydrogeological aspects, combined with effective engineering practices, can significantly improve the city’s flood control capacity. These measures can solve the problem of the “once-in-a-millennium” occurrence of torrential rain disasters such as the “720” torrential rainstorm that has affected the city of Zhengzhou.
Technological Composition and Innovation Factors in Inventive Yangtze River Delta: Evidence from Patent Inventions
Authors: Li Lingyue , Wang Lie , Zhang Xiaohu , Wang Lan
Published: February 2024

Patents as proxy for technological trends is well noted. The rapid increase of patents in China, however, has aroused debates on its technological progress: ‘few original innovations’ are produced in advanced areas, and true ‘breakthroughs’ are disproportionate to the quantity of the applications. As different technological fields contributions vary to technological progress, a nuanced understanding towards technological composition is in need to help reveal China’s strength in technological innovation. This research takes the Yangtze River Delta (YRD), one of China’s most inventive city-regions, as an epitome to examine the issue via three steps: (1) valid patent inventions applied from 2010 to 2018 are sorted to capture the concentration and colocation features of 35 technological fields defined by the World Intellectual Property Organization (WIPO); (2) four types (intensive, extensive, distinctive, and supportive) of technologies exemplifying technology intensity and interactivity are identified by the cross-classification method and further analyzed by spatial autocorrelation; (3) how urban factors relate to innovation of these four types of technologies are explored. This research unveils a mixed but polarized structure of technological composition in the YRD where the spatial concentration of technologies is as analogous to the nation’s but colocation is not; though quite a few technologies fall into the intensive (usually high-tech) category which assumes to be more likely to breed ‘breakthroughs’, their numbers are limited and far less than extensive (usually labor intensive) or supportive. Knowledge exchange is frequent in core inventive cities where economic performance measured by GDP is most eminently linked to patent inventions of categorized technologies, the exception is intensive technology for which the significance of university students overrides other factors.
Land-Cover Classification Using Deep Learning with High-Resolution Remote-Sensing Imagery
Authors: Fayaz Muhammad , Nam Junyoung , Dang L. Minh , Song Hyoung-Kyu , Moon Hyeonjoon
Published: February 2024

Land-area classification (LAC) research offers a promising avenue to address the intricacies of urban planning, agricultural zoning, and environmental monitoring, with a specific focus on urban areas and their complex land usage patterns. The potential of LAC research is significantly propelled by advancements in high-resolution satellite imagery and machine learning strategies, particularly the use of convolutional neural networks (CNNs). Accurate LAC is paramount for informed urban development and effective land management. Traditional remote-sensing methods encounter limitations in precisely classifying dynamic and complex urban land areas. Therefore, in this study, we investigated the application of transfer learning with Inception-v3 and DenseNet121 architectures to establish a reliable LAC system for identifying urban land use classes. Leveraging transfer learning with these models provided distinct advantages, as it allows the LAC system to benefit from pre-trained features on large datasets, enhancing model generalization and performance compared to starting from scratch. Transfer learning also facilitates the effective utilization of limited labeled data for fine-tuning, making it a valuable strategy for optimizing model accuracy in complex urban land classification tasks. Moreover, we strategically employ fine-tuned versions of Inception-v3 and DenseNet121 networks, emphasizing the transformative impact of these architectures. The fine-tuning process enables the model to leverage pre-existing knowledge from extensive datasets, enhancing its adaptability to the intricacies of LC classification. By aligning with these advanced techniques, our research not only contributes to the evolution of remote-sensing methodologies but also underscores the paramount importance of incorporating cutting-edge methodologies, such as fine-tuning and the use of specific network architectures, in the continual enhancement of LC classification systems. Through experiments conducted on the UC-Merced_LandUse dataset, we demonstrate the effectiveness of our approach, achieving remarkable results, including 92% accuracy, 93% recall, 92% precision, and a 92% F1-score. Moreover, employing heatmap analysis further elucidates the decision-making process of the models, providing insights into the classification mechanism. The successful application of CNNs in LAC, coupled with heatmap analysis, opens promising avenues for enhanced urban planning, agricultural zoning, and environmental monitoring through more accurate and automated land-area classification.
Special Issue on Fatigue, Performance, and Damage Assessments of Concrete
Authors: Yang Sungchul
Published: February 2024

This Special Issue covers the latest research on fatigue, performance, and damage assessments of concrete. Concrete fatigue is known as a phenomenon characterized by the repetition of loads. The fatigue-based performance of concrete may be affected by a combination of diverse loads, mechanical strength properties, and environmental changes. These factors eventually lead to poor concrete performance. In this Special Issue, nine papers were accepted, divided into three subgroups: two papers on fatigue, two papers on performance, and five papers on damage assessment. Unlike articles published in past Special Issues, our Special Issue contains papers that address concrete performance in concrete pavement applications. In particular, six of the articles contained in this issue concentrate on pavement performance and damage assessments, especially in terms of the Pavement Condition Index. Together with a brief introduction, the keywords, research significance and potential impacts of each article are summarized in this Editorial.
Spanishness and Race in North American Monumental Architecture
Authors: Beck Lauren
Published: February 2024

The representation of Spain, and Spanishness in general, at sites of collective identity in the United States and Canada requires scholarly attention. Many monuments, which range from statues and museums to capitol buildings and national parks, continue to commemorate colonial times despite broader public awareness of the association between colonization and racialized violence, as well as the explicit movement toward decolonization. This commemorative material also demonstrates how non-Spanish settlers have appropriated historical moorings of Spain and its colonial past to reinforce and whitewash their identities in places such as New Mexico and Texas, and even in Newfoundland and Labrador. How monuments are funded and gain public support is another vector that points to the ways that identity—particularly, white identity—informs monumental architecture in ways that exclude people of colour, as well as women, who, when featured in monuments, are usually dehumanized as concepts rather than being the actors of settler-colonialism. This article explores these challenging topics with the aim of articulating a roadmap for future scholarship on this subject.
Atmospheric Processes over the Broader Mediterranean Region: Effect of the El Niño–Southern Oscillation?
Authors: Kambezidis Harry D.
Published: February 2024

The Mediterranean area is considered a hot spot on our planet because it represents the crossroads of various aerosols. Several studies have shown that the weather in the region is affected by the North-Atlantic Oscillation, which, in turn, is well connected with the El Niño–Southern Oscillation (ENSO) phenomenon. Nevertheless, no study has investigated the ENSO effect on the solar radiation and atmospheric aerosols in this region. The present study considers a greater area around the Mediterranean Sea over the period 1980–2022. The results show that there exists a loose but significant dependence, in some cases, of the optical properties of aerosols (aerosol optical depth, Ångström exponent, cloud optical depth) and solar radiation (net short-wave and net long-wave radiation, direct aerosol radiative forcing) on ENSO events. The results of this study provide motivation for further investigations, since such results can increase the accuracy of general circulation models that deal with climate change. Besides the ENSO effect, the enrichment of the Mediterranean atmosphere in suspended particles from great volcanic eruptions is shown. The inter-annual variation of the examined parameters is presented. A classification of the existing aerosols over the area is also provided.
The Assessment of PM2.5 and PM10 Immission in Atmospheric Air in a Climate Chamber during Tests of an Electric Car on a Chassis Dynamometer
Authors: Jaworski Artur , Balawender Krzysztof , Kuszewski Hubert , Jaremcio Mirosław
Published: February 2024

Electric cars, like internal combustion vehicles, emit particulate pollution from non-exhaust systems, i.e., tires and brakes, which is included in the Euro 7 emission standard planned for implementation. Tests conducted on chassis dynamometers are accompanied by particulate emissions from non-exhaust systems, which are introduced into the ambient air on the test bench. Particulate emissions tests from non-engine systems on chassis dynamometers are mainly aimed at measuring the mass or number of particulates from tires and brakes. In contrast, little attention is paid to the immission of particulate matter from tires and brakes on the dynamometer during tests, which in the case of electric cars include, for example, measurements of energy consumption or range. Therefore, in order to draw attention to the problem of these emissions, the authors carried out measurements of PM2.5 and PM10 immissions into the air in the climatic chamber during tests of an electric car on a chassis dynamometer. The car tests were carried out in accordance with the WLTC (Worldwide harmonized Light duty Test Cycle) and at constant speed. Based on the test results, a model was proposed for the immission of particulate matter in laboratory air from tire and brake abrasion, taking traffic parameters into account. The results and the developed model show that air quality, in terms of particulate content, deteriorates significantly during testing.
Autosomal Recessive Non-Syndromic Deafness: Is AAV Gene Therapy a Real Chance?
Authors: Brotto Davide , Greggio Marco , De Filippis Cosimo , Trevisi Patrizia
Published: February 2024

The etiology of sensorineural hearing loss is heavily influenced by genetic mutations, with approximately 80% of cases attributed to genetic causes and only 20% to environmental factors. Over 100 non-syndromic deafness genes have been identified in humans thus far. In non-syndromic sensorineural hearing impairment, around 75–85% of cases follow an autosomal recessive inheritance pattern. In recent years, groundbreaking advancements in molecular gene therapy for inner-ear disorders have shown promising results. Experimental studies have demonstrated improvements in hearing following a single local injection of adeno-associated virus-derived vectors carrying an additional normal gene or using ribozymes to modify the genome. These pioneering approaches have opened new possibilities for potential therapeutic interventions. Following the PRISMA criteria, we summarized the AAV gene therapy experiments showing hearing improvement in the preclinical phases of development in different animal models of DFNB deafness and the AAV gene therapy programs currently in clinical phases targeting autosomal recessive non syndromic hearing loss. A total of 17 preclinical studies and 3 clinical studies were found and listed. Despite the hurdles, there have been significant breakthroughs in the path of HL gene therapy, holding great potential for providing patients with novel and effective treatment.
On Universality of Some Beurling Zeta-Functions
Authors: Geštautas Andrius , Laurinčikas Antanas
Published: February 2024

Let P be the set of generalized prime numbers, and ζP(s), s=σ+it, denote the Beurling zeta-function associated with P. In the paper, we consider the approximation of analytic functions by using shifts ζP(s+iτ), τ∈R. We assume the classical axioms for the number of generalized integers and the mean of the generalized von Mangoldt function, the linear independence of the set {logp:p∈P}, and the existence of a bounded mean square for ζP(s). Under the above hypotheses, we obtain the universality of the function ζP(s). This means that the set of shifts ζP(s+iτ) approximating a given analytic function defined on a certain strip σ^<σ<1 has a positive lower density. This result opens a new chapter in the theory of Beurling zeta functions. Moreover, it supports the Linnik–Ibragimov conjecture on the universality of Dirichlet series. For the proof, a probabilistic approach is applied.
Comparison of Bagging and Sparcity Methods for Connectivity Reduction in Spiking Neural Networks with Memristive Plasticity
Authors: Rybka Roman , Davydov Yury , Vlasov Danila , Serenko Alexey , Sboev Alexander , Ilyin Vyacheslav
Published: February 2024

Developing a spiking neural network architecture that could prospectively be trained on energy-efficient neuromorphic hardware to solve various data analysis tasks requires satisfying the limitations of prospective analog or digital hardware, i.e., local learning and limited numbers of connections, respectively. In this work, we compare two methods of connectivity reduction that are applicable to spiking networks with local plasticity; instead of a large fully-connected network (which is used as the baseline for comparison), we employ either an ensemble of independent small networks or a network with probabilistic sparse connectivity. We evaluate both of these methods with a three-layer spiking neural network, which are applied to handwritten and spoken digit classification tasks using two memristive plasticity models and the classical spike time-dependent plasticity (STDP) rule. Both methods achieve an F1-score of 0.93–0.95 on the handwritten digits recognition task and 0.85–0.93 on the spoken digits recognition task. Applying a combination of both methods made it possible to obtain highly accurate models while reducing the number of connections by more than three times compared to the basic model.
Optimization of Platelet-Rich Plasma Preparation for Regenerative Medicine: Comparison of Different Anticoagulants and Resuspension Media
Authors: Carvalho Alexandra , Ferreira Ana Filipa , Soares Maria , Santos Susana , Tomé Patrícia , Machado-Simões Juliana , Pais Ana Sofia , Sousa Ana Paula , Paiva Artur , Almeida-Santos Teresa
Published: February 2024

Platelet-rich plasma (PRP) has emerged as a promising therapy in regenerative medicine. However, the lack of standardization in PRP preparation protocols presents a challenge in achieving reproducible and accurate results. This study aimed to optimize the PRP preparation protocol by investigating the impact of two different anticoagulants, sodium citrate (SC) and ethylenediaminetetraacetic acid (EDTA), and resuspension media, plasma versus sodium chloride (NaCl). Platelet recovery rates were calculated and compared between groups, in addition to platelet activity and vascular endothelial growth factor (VEGF) released into plasma after PRP activation. The platelet recovery rate was higher with EDTA in comparison to SC (51.04% vs. 29.85%, p = 0.005). Platelet activity was also higher, with a higher expression of two platelet antibodies, platelet surface P-Selectin (CD62p) and PAC-1, in the EDTA group. The concentration of VEGF was higher with SC in comparison to EDTA (628.73 vs. 265.44 pg/mL, p = 0.013). Platelet recovery rates and VEGF levels were higher in PRP resuspended in plasma when compared to NaCl (61.60% vs. 48.61%, p = 0.011 and 363.32 vs. 159.83 pg/mL, p = 0.005, respectively). Our study reinforces the superiority of EDTA (as anticoagulant) and plasma (for resuspension) in obtaining a higher platelet recovery and preserving platelet functionality during PRP preparation.
Regulation of Oxygen Tension as a Strategy to Control Chondrocytic Phenotype for Cartilage Tissue Engineering and Regeneration
Authors: Lammi Mikko J. , Qu Chengjuan
Published: February 2024

Cartilage defects and osteoarthritis are health problems which are major burdens on health care systems globally, especially in aging populations. Cartilage is a vulnerable tissue, which generally faces a progressive degenerative process when injured. This makes it the 11th most common cause of global disability. Conservative methods are used to treat the initial phases of the illness, while orthopedic management is the method used for more progressed phases. These include, for instance, arthroscopic shaving, microfracturing and mosaicplasty, and joint replacement as the final treatment. Cell-based implantation methods have also been developed. Despite reports of successful treatments, they often suffer from the non-optimal nature of chondrocyte phenotype in the repair tissue. Thus, improved strategies to control the phenotype of the regenerating cells are needed. Avascular tissue cartilage relies on diffusion for nutrients acquisition and the removal of metabolic waste products. A low oxygen content is also present in cartilage, and the chondrocytes are, in fact, well adapted to it. Therefore, this raises an idea that the regulation of oxygen tension could be a strategy to control the chondrocyte phenotype expression, important in cartilage tissue for regenerative purposes. This narrative review discusses the aspects related to oxygen tension in the metabolism and regulation of articular and growth plate chondrocytes and progenitor cell phenotypes, and the role of some microenvironmental factors as regulators of chondrocytes.
Influence of Bioceramic Cements on the Quality of Obturation of the Immature Tooth: An In Vitro Microscopic and Tomographic Study
Authors: Al-Rayesse Raya , Al-Jabban Ossama , Eid Ammar , Kabtoleh Alaa , Addiego Frédéric , Mancino Davide , Haikel Youssef , Kharouf Naji
Published: February 2024

The present in vitro study focuses on the filling ability of three different bioceramic cements with or without the addition of a bioceramic sealer in an open apex model on the marginal apical adaptation, tubule infiltrations, and void distributions as well as the interface between the cement and the sealer materials. To this end, sixty mandibular premolars were used. MTA-Biorep (BR), Biodentine (BD), and Well-Root Putty (WR) were used to obturate the open apex model with or without the addition of a bioceramic sealer, namely TotalFill® BC sealer™ (TF). A digital optical microscope and scanning electron microscope (SEM) were used to investigate the cement–dentin interface, marginal apical adaptation, and the material infiltration into the dentinal tubules. Micro-computed X-ray tomography and digital optical microscopy were used to investigate the cement–sealer interface. The results were analyzed by using the Kruskal–Wallis test. No significant difference was found between the groups for the marginal apical adaptation quality (p > 0.05). Good adaptation of the dentin–cement interface was found for all tested groups and the sealer was placed between the cement material and dentinal walls. All the groups demonstrated some infiltrations into the dentinal tubules at the coronal part except for the BR group. A good internal interface was found between the cement and the sealer with the presence of voids at the external interface. A larger number of voids were found in the case of the BD-TF group compared to each of the other two groups (p < 0.05). Within the limitations of the present in vitro study, all the groups demonstrated good marginal apical adaptation. The use of a sealer in an open apex does not guarantee good filling and, in addition, creates voids at the external interfaces with the dental walls when the premixed sealer is used with powder–liquid cement systems. The use of a premixed bioceramic cement could offer fewer complications than when a powder–liquid cement system is used.
Monoclonal Antibody Development for Cancer Treatment Using the Phage Display Library Platform
Authors: Zhang Tiantian , Wang Zhe
Published: February 2024

Thirty-four years ago, the groundbreaking work of John McCafferty and Sir Gregory Winter in developing phage display technology revolutionized the discovery of human antibodies, paving the way for diverse applications. Since then, numerous phage-derived antibodies have been successfully developed and advanced into clinical studies, resulting in the approval of more than a dozen therapeutic antibodies. These antibodies have demonstrated efficacy across a spectrum of medical conditions, ranging from autoimmune diseases to various cancers. In this article, we provide an in-depth review of the development of phage display libraries as powerful platforms for therapeutic antibody discovery, elucidating the intricate procedures involved in antibody development. Additionally, we conduct a review of the current ntibody drugs for cancer treatment that have been developed using the phage display platform. Furthermore, we discuss the challenges inherent in this technology, offering insights into potential solutions to enhance crucial steps and facilitate more efficient drug discovery in the field of phage display technology.
An Innovative Inducer of Platelet Production, Isochlorogenic Acid A, Is Uncovered through the Application of Deep Neural Networks
Authors: Yi Taian , Luo Jiesi , Liao Ruixue , Wang Long , Wu Anguo , Li Yueyue , Zhou Ling , Ni Chengyang , Wang Kai , Tang Xiaoqin , Zou Wenjun , Wu Jianming
Published: February 2024

(1) Background: Radiation-induced thrombocytopenia (RIT) often occurs in cancer patients undergoing radiation therapy, which can result in morbidity and even death. However, a notable deficiency exists in the availability of specific drugs designed for the treatment of RIT. (2) Methods: In our pursuit of new drugs for RIT treatment, we employed three deep learning (DL) algorithms: convolutional neural network (CNN), deep neural network (DNN), and a hybrid neural network that combines the computational characteristics of the two. These algorithms construct computational models that can screen compounds for drug activity by utilizing the distinct physicochemical properties of the molecules. The best model underwent testing using a set of 10 drugs endorsed by the US Food and Drug Administration (FDA) specifically for the treatment of thrombocytopenia. (3) Results: The Hybrid CNN+DNN (HCD) model demonstrated the most effective predictive performance on the test dataset, achieving an accuracy of 98.3% and a precision of 97.0%. Both metrics surpassed the performance of the other models, and the model predicted that seven FDA drugs would exhibit activity. Isochlorogenic acid A, identified through screening the Chinese Pharmacopoeia Natural Product Library, was subsequently subjected to experimental verification. The results indicated a substantial enhancement in the differentiation and maturation of megakaryocytes (MKs), along with a notable increase in platelet production. (4) Conclusions: This underscores the potential therapeutic efficacy of isochlorogenic acid A in addressing RIT.
Charting the Course in Sequencing Antibody-Drug Conjugates in Breast Cancer
Authors: Saltalamacchia Giuseppe , Torrisi Rosalba , De Sanctis Rita , Masci Giovanna , Miggiano Chiara , Gaudio Mariangela , Benvenuti Chiara , Jacobs Flavia , Gerosa Riccardo , Santoro Armando , Zambelli Alberto
Published: February 2024

Based on the unprecedented results observed in recent clinical trials, antibody-drug conjugates (ADCs) have revolutionized the treatment algorithm of metastatic breast cancer (mBC). The strategy of sequencing different ADCs in other lines of therapy is highly attractive, but the proportion of patients who have undergone such a strategy in the context of published clinical trials is still limited, especially for modern ADCs. HER2-positive disease is primarily managed with a sequence of different ADCs. Historically, trastuzumab emtansine (T-DM1) has been the most commonly used ADC for both early and metastatic HER2-positive disease. Considering the recent evidence related to trastuzumab deruxtecan (T-DXd), it is expected to assume the role of the main ADC in our clinical practice. Herein, we report a retrospective analysis of the sequence of different ADCs relying on available published data from clinical trials.
Use of Oleuropein and Hydroxytyrosol for Cancer Prevention and Treatment: Considerations about How Bioavailability and Metabolism Impact Their Adoption in Clinical Routine
Authors: Gervasi Francesco , Pojero Fanny
Published: February 2024

The fact that the Mediterranean diet could represent a source of natural compounds with cancer-preventive and therapeutic activity has been the object of great interest, especially with regard to the mechanisms of action of polyphenols found in olive oil and olive leaves. Secoiridoid oleuropein (OLE) and its derivative hydroxytyrosol (3,4-dihydroxyphenylethanol, HT) have demonstrated anti-proliferative properties against a variety of tumors and hematological malignancies both in vivo and in vitro, with measurable effects on cellular redox status, metabolism, and transcriptional activity. With this review, we aim to summarize the most up-to-date information on the potential use of OLE and HT for cancer treatment, making important considerations about OLE and HT bioavailability, OLE- and HT-mediated effects on drug metabolism, and OLE and HT dual activity as both pro- and antioxidants, likely hampering their use in clinical routine. Also, we focus on the details available on the effects of nutritionally relevant concentrations of OLE and HT on cell viability, redox homeostasis, and inflammation in order to evaluate if both compounds could be considered cancer-preventive agents or new potential chemotherapy drugs whenever their only source is represented by diet.
Comprehensive Transcriptomic Profiling of Diverse Brain Tumor Types Uncovers Complex Structures of the Brain Tumor Microenvironment
Authors: Choi Jiin , Cho Hee Jin
Published: February 2024

Various types of brain tumors occur in both children and adults. These tumors manifest with different characteristics such as malignancy, cellular lineage, location of origin, and genomic profile. Recently, immunotherapy, which manipulates immune cells in the tumor microenvironment (TME) to kill tumor cells, has attracted attention as a treatment strategy for tumors. Here, we analyzed the transcriptomic architecture of the brain tumor microenvironment to provide potential guidelines to overcome the therapeutic vulnerabilities to brain tumors. We decomposed the cellular populations of six brain tumor types (meningioma, pilocytic astrocytoma, ependymoma, medulloblastoma, glioblastoma, and lower-grade glioma) using publicly available microarray data and single-cell RNA sequencing (scRNA-seq) data. Interestingly, transcriptome-based immune cell profiling revealed that infiltrating immune cell types in the brain TME, particularly M2 macrophages, CD8+ T cells, and CD4+ T cells, could be distinguished by tumor type, malignancy, and location. scRNA-seq revealed differences in the proportions of dendritic and mural cells. Unsupervised clustering using immune-related genes divided all samples into two distinct clusters with different characteristics. In addition, immune subpopulations showed disparate reactions after anti-PD-1 therapy for glioblastoma. Our results unveiled the distinct TME across brain tumor types and provided a transcriptomic landscape. Our findings may contribute to realizing future precision medicine, providing a basic rationale for the therapeutics of brain tumors.
The Assessment of a Novel Endoscopic Ultrasound-Compatible Cryocatheter to Ablate Pancreatic Cancer
Authors: Baust John M. , Robilotto Anthony , Raijman Isaac , Santucci Kimberly L. , Van Buskirk Robert G. , Baust John G. , Snyder Kristi K.
Published: February 2024

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease that may be treated utilizing thermal therapies. Cryoablation is an effective, minimally invasive therapy that has been utilized for the treatment of various cancers, offering patients a quicker recovery and reduced side effects. Cryoablation has been utilized on a limited basis for the treatment of PDAC. With the recent reports on the success of cryoablation, there is a growing interest in the use of cryoablation as a standalone, minimally invasive procedure to treat PDAC. While offering a promising path, the application of cryoablation to PDAC is limited by current technologies. As such, there is a need for the development of new devices to support advanced treatment strategies for PDAC. To this end, this study investigated the performance of a new endoscopic ultrasound-compatible cryoablation catheter technology, FrostBite. We hypothesized that FrostBite would enable the rapid, effective, minimally invasive delivery of ultra-cold temperatures to target tissues, resulting in effective ablation via an endoscopic approach. Thermal properties and ablative efficacy were evaluated using a heat-loaded gel model, tissue-engineered models (TEMs), and an initial in vivo porcine study. Freeze protocols evaluated included single and repeat 3 and 5 min applications. Isotherm assessment revealed the generation of a 2.2 cm diameter frozen mass with the −20 °C isotherm reaching a diameter of 1.5 cm following a single 5 min freeze. TEM studies revealed the achievement of temperatures ≤ −20 °C at a diameter of 1.9 cm after a 5 min freeze. Fluorescent imaging conducted 24 h post-thaw demonstrated a uniformly shaped ellipsoidal ablative zone with a midline diameter of 2.5 cm, resulting in a total ablative volume of 6.9 cm3 after a single 5 min freeze. In vivo findings consistently demonstrated the generation of ablative areas measuring 2.03 cm × 3.2 cm. These studies demonstrate the potential of the FrostBite cryocatheter as an endoscopic ultrasound-based treatment option. The data suggest that FrostBite may provide for the rapid, effective, controllable freezing of cancerous pancreatic and liver tissues. This ablative power also offers the potential of improved safety margins via the minimally invasive nature of an endoscopic ultrasound-based approach or natural orifice transluminal endoscopic surgery (NOTES)-based approach. The results of this pre-clinical feasibility study show promise, affirming the need for further investigation into the potential of the FrostBite cryocatheter as an advanced, minimally invasive cryoablative technology.
Machine Learning Approach to Identify Case-Control Studies on ApoE Gene Mutations Linked to Alzheimer’s Disease in Italy
Authors: Saraceno Giorgia Francesca , Abrego-Guandique Diana Marisol , Cannataro Roberto , Caroleo Maria Cristina , Cione Erika
Published: February 2024

Background: An application of artificial intelligence is machine learning, which allows computer programs to learn and create data. Methods: In this work, we aimed to evaluate the performance of the MySLR machine learning platform, which implements the Latent Dirichlet Allocation (LDA) algorithm in the identification and screening of papers present in the literature that focus on mutations of the apolipoprotein E (ApoE) gene in Italian Alzheimer’s Disease patients. Results: MySLR excludes duplicates and creates topics. MySLR was applied to analyze a set of 164 scientific publications. After duplicate removal, the results allowed us to identify 92 papers divided into two relevant topics characterizing the investigated research area. Topic 1 contains 70 papers, and topic 2 contains the remaining 22. Despite the current limitations, the available evidence suggests that articles containing studies on Italian Alzheimer’s Disease (AD) patients were 65.22% (n = 60). Furthermore, the presence of papers about mutations, including single nucleotide polymorphisms (SNPs) ApoE gene, the primary genetic risk factor of AD, for the Italian population was 5.4% (n = 5). Conclusion: The results show that the machine learning platform helped to identify case-control studies on ApoE gene mutations, including SNPs, but not only conducted in Italy.
A Bio-Inspired Probabilistic Neural Network Model for Noise-Resistant Collision Perception
Authors: Hong Jialan , Sun Xuelong , Peng Jigen , Fu Qinbing
Published: February 2024

Bio-inspired models based on the lobula giant movement detector (LGMD) in the locust’s visual brain have received extensive attention and application for collision perception in various scenarios. These models offer advantages such as low power consumption and high computational efficiency in visual processing. However, current LGMD-based computational models, typically organized as four-layered neural networks, often encounter challenges related to noisy signals, particularly in complex dynamic environments. Biological studies have unveiled the intrinsic stochastic nature of synaptic transmission, which can aid neural computation in mitigating noise. In alignment with these biological findings, this paper introduces a probabilistic LGMD (Prob-LGMD) model that incorporates a probability into the synaptic connections between multiple layers, thereby capturing the uncertainty in signal transmission, interaction, and integration among neurons. Comparative testing of the proposed Prob-LGMD model and two conventional LGMD models was conducted using a range of visual stimuli, including indoor structured scenes and complex outdoor scenes, all subject to artificial noise. Additionally, the model’s performance was compared to standard engineering noise-filtering methods. The results clearly demonstrate that the proposed model outperforms all comparative methods, exhibiting a significant improvement in noise tolerance. This study showcases a straightforward yet effective approach to enhance collision perception in noisy environments.
Botox Optimization Algorithm: A New Human-Based Metaheuristic Algorithm for Solving Optimization Problems
Authors: Hubálovská Marie , Hubálovský Štěpán , Trojovský Pavel
Published: February 2024

This paper introduces the Botox Optimization Algorithm (BOA), a novel metaheuristic inspired by the Botox operation mechanism. The algorithm is designed to address optimization problems, utilizing a human-based approach. Taking cues from Botox procedures, where defects are targeted and treated to enhance beauty, the BOA is formulated and mathematically modeled. Evaluation on the CEC 2017 test suite showcases the BOA’s ability to balance exploration and exploitation, delivering competitive solutions. Comparative analysis against twelve well-known metaheuristic algorithms demonstrates the BOA’s superior performance across various benchmark functions, with statistically significant advantages. Moreover, application to constrained optimization problems from the CEC 2011 test suite highlights the BOA’s effectiveness in real-world optimization tasks.