bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-Sample Detection of Soil Nitrate Nitrogen Using a Digital Microfluidic Platform
Authors: Hong Yan , Xia Zhihao , Su Jingming , Wang Rujing , Chang Yongjia , Huang Qing , Wei Liman , Chen Xiangyu
Published: December 2023

The rapid quantification of nitrate nitrogen concentration plays a pivotal role in monitoring soil nutrient content. Nevertheless, the low detection efficiency limits the application of traditional methods in rapid testing. For this investigation, we utilized a digital microfluidic platform and 3D-printed microfluidics to accomplish automated detection of soil nitrate nitrogen with high sensitivity across numerous samples. The system combines digital microfluidics (DMF), 3D-printed microfluidics, a peristaltic pump, and a spectrometer. The soil solution, obtained after extraction, was dispensed onto the digital microfluidic platform using a micropipette. The digital microfluidic platform regulated the movement of droplets until they reached the injection area, where they were then aspirated into the 3D-printed microfluidic device for absorbance detection. Implementing this approach allows for the convenient sequential testing of multi-samples, thereby enhancing the efficiency of nitrate nitrogen detection. The results demonstrate that the device exhibits rapid detection (200 s for three samples), low reagent consumption (40 µL per sample), and low detection limit (95 µg/L). In addition, the relative error between the detected concentration and the concentration measured by ultraviolet spectrophotometry is kept within 20%, and the relative standard deviation (RSD) of the measured soil samples is between 0.9% and 4.7%. In the foreseeable future, this device will play a significant role in improving the efficiency of soil nutrient detection and guiding fertilization practices.
TinyML Olive Fruit Variety Classification by Means of Convolutional Neural Networks on IoT Edge Devices
Authors: Hayajneh Ali M. , Batayneh Sahel , Alzoubi Eyad , Alwedyan Motasem
Published: December 2023

Machine learning (ML) within the edge internet of things (IoT) is instrumental in making significant shifts in various industrial domains, including smart farming. To increase the efficiency of farming operations and ensure ML accessibility for both small and large-scale farming, the need for a low-cost ML-enabled framework is more pressing. In this paper, we present an end-to-end solution that utilizes tiny ML (TinyML) for the low-cost adoption of ML in classification tasks with a focus on the post-harvest process of olive fruits. We performed dataset collection to build a dataset that consists of several varieties of olive fruits, with the aim of automating the classification and sorting of these fruits. We employed simple image segmentation techniques by means of morphological segmentation to create a dataset that consists of more than 16,500 individually labeled fruits. Then, a convolutional neural network (CNN) was trained on this dataset to classify the quality and category of the fruits, thereby enhancing the efficiency of the olive post-harvesting process. The goal of this study is to show the feasibility of compressing ML models into low-cost edge devices with computationally constrained settings for tasks like olive fruit classification. The trained CNN was efficiently compressed to fit into a low-cost edge controller, maintaining a small model size suitable for edge computing. The performance of this CNN model on the edge device, focusing on metrics like inference time and memory requirements, demonstrated its feasibility with an accuracy of classification of more than 97.0% and minimal edge inference delays ranging from 6 to 55 inferences per second. In summary, the results of this study present a framework that is feasible and efficient for compressing CNN models on edge devices, which can be utilized and expanded in many agricultural applications and also show the practical insights for implementing the used CNN architectures into edge IoT devices and show the trade-offs for employing them using TinyML.
Factors Associated with SARS-CoV-2 Infection Evaluated by Antibody Response in a Sample of Workers from the Emilia-Romagna Region, Northern Italy
Authors: Paduano Stefania , Granata Michele , Turchi Sara , Modenese Alberto , Galante Pasquale , Poggi Alessandro , Marchesi Isabella , Frezza Giuseppina , Dervishaj Giulia , Vivoli Roberto , Verri Sara , Marchetti Simona , Gobba Fabriziomaria , Bargellini Annalisa
Published: December 2023

Factors associated with SARS-CoV-2 infection risk are still debated. This case–control study aims to investigate the possible relationship between SARS-CoV-2 infection, evaluated through antibody response, and the main sociodemographic, occupational, clinical-anamnestic, and biochemical factors in a population of Modena province (Northern Italy), mainly workers. Both workers who voluntarily joined the screening campaign proposed by companies and self-referred individuals who underwent serological testing were enrolled. Subjects with antibody positivity were recruited as cases (n = 166) and subjects tested negative (n = 239) as controls. A questionnaire on sociodemographic, occupational, and clinical data was administered through telephone interviews. Serum zinc/iron/copper/chromium/nickel, vitamins D/B12, folates, triglycerides, and LDL/HDL/total cholesterol were measured. Cases lived more often in urban areas (61.8% vs. 57%). Cases and controls did not differ significantly by working macrocategories, but the percentage of workers in the ceramic sector was higher among cases. Low adherence to preventive measures in the workplace was more frequent among seropositives. Folate concentration was significantly lower among cases. Therefore, adequate folate levels, living in rural areas, and good adherence to preventive strategies seem protective against infection. Workers in the ceramic sector seem to be at greater risk; specific factors involved are not defined, but preventive interventions are needed.
A Literature Review on the Charging Behaviour of Private Electric Vehicles
Authors: Andrenacci Natascia , Valentini Maria Pia
Published: December 2023

Electric mobility is one of the ways of containing greenhouse gas and local pollutants emissions in urban areas. Nevertheless, the massive introduction of battery-powered electric vehicles (EVs) is introducing some concerns related to their energy demand. Modelling vehicle usage and charging behavior is essential for charge demand forecasting and energy consumption estimation. Therefore, it is crucial to understand how the charging decisions of EV owners are influenced by different factors, ranging from the charging infrastructure characteristics to the users’ profiles. This review examines the approaches used to investigate charging behavior and highlights the trends and differences between the results, remarking on any gaps worthy of further investigation.
A Neural Network Approach to a Grayscale Image-Based Multi-File Type Malware Detection System
Authors: Copiaco Abigail , El Neel Leena , Nazzal Tasnim , Mukhtar Husameldin , Obaid Walid
Published: December 2023

This study introduces an innovative all-in-one malware identification model that significantly enhances convenience and resource efficiency in classifying malware across diverse file types. Traditional malware identification methods involve the extraction of static and dynamic features, followed by comparisons with signature-based databases or machine learning-based classifiers. However, many malware detection applications that rely on transfer learning and image transformation suffer from excessive resource consumption. In recent years, transfer learning has emerged as a powerful tool for developing effective classifiers, leveraging pre-trained neural network models. In this research, we comprehensively explore various pre-trained network architectures, including compact and conventional networks, as well as series and directed acyclic graph configurations for malware classification. Our approach utilizes grayscale transform-based features as a standardized set of characteristics, streamlining malware classification across various file types. To ensure the robustness and generalization of our classification models, we integrate multiple datasets into the training process. Remarkably, we achieve an optimal model with 96% accuracy, while maintaining a modest 5 MB size using the SqueezeNet classifier. Overall, our model efficiently classifies malware across file types, reducing the computational load, which can be useful for cybersecurity professionals and organizations.
Study on the Seismic Response of Shield Tunnel Structures with the Preload Loss of Bolts
Authors: Cui Hongzhi , Tao Ran , Shen Jun , Wu Xianlong , Bao Xiaohua , Liu Ziming , Chen Xiangsheng
Published: December 2023

Shield tunnels can experience preload loss in their connecting bolts during the operational phase, leading to changes in tunnel structure stiffness, which, in turn, affect the seismic performance of shield tunnels. A refined three-dimensional model of shield tunnel was established using the finite element method to study the impact of preload loss in connecting bolts on the seismic dynamic response of shield tunnels. An artificial viscoelastic boundary was used to simulate the propagation of seismic waves from an infinitely distant field. This study investigated the effects of different levels of preload loss on the seismic response of shield tunnels. In addition, the Arias intensity, which can reflect the degree of seismic impact on structures, was used to analyse the extent of damage to the tunnel. The conclusions drawn from the study are as follows: As the level of preload loss increases, the tightness of the segments during the static phase gradually deteriorates, and the maximum joint opening during the seismic loading phase continues to increase. Post-earthquake non-recoverable ellipticity and radial deformation progressively increase with an increase to preload loss level. Overall tunnel damage becomes more significant with the degree of preload loss increases depending on the Arias intensity. Preload loss leads to a decrease in the overall structural stiffness and an increase in longitudinal relative displacement. In conclusion, preload loss also affects structural failure mode and seismic performance. These research findings are of reference value for enhancing the seismic performance of shield tunnel structures and ensuring engineering safety.
Nanomaterials Applied in the Construction Sector: Environmental, Human Health, and Economic Indicators
Authors: Ferreira Maria Teresa , Soldado Eliana , Borsoi Giovanni , Mendes Maria Paula , Flores-Colen Inês
Published: December 2023

Over the past two decades, the application of nanostructured materials in construction, such as concrete, paint, coatings, glass, renders, plasters, thermal insulation, steel, and even sensors, has become increasingly prevalent. However, previous studies and reports have raised concerns about the ecotoxicity and long-term impact of nanomaterials on human health and the environment. National and international legislation and regulations are struggling to keep up with the rapid development of nanomaterials, taking into account their unique characteristics and essential requirements for application and commercialization. This paper, based on existing standards for conventional materials and bibliometric networks of papers focused on nanomaterials, conducts a critical review and proposes relevant indicators for the application of nanomaterials in the construction sector. These indicators should be mandatory and are divided into environmental, human health, and economic perspectives, providing a risk assessment framework for applying nanomaterial-based constructive solutions oriented to environmental, social, and economic sustainability.
Development of Effective Infrared Reflective Coatings
Authors: Mara Józsefné , Bodnár Attila-Ede , Trif László , Telegdi Judit
Published: December 2023

The adsorption of surfaces exposed to sunlight results in increased temperatures that can cause physical damage and an increase in energy consumption. Infrared reflective coatings can keep objects cooler and have significant benefits in a wide variety of application by reflecting infrared light and decreasing heat, reducing operating costs, improving energy efficiency in buildings and vehicles, and extending an objects’ lifespan. The main aim of our research was to develop coatings in a RAL7016 Anthracite grey color with minimum heat adsorption in the infrared wavelength range. This was achieved using a combination of infrared transparent and infrared reflective pigment built-in coatings applied on two primers: white and black. Infrared reflectivity or transparency, as well as surface temperature, was investigated as a function of the composition and concentration of pigments. These coatings were characterized by chromatic parameters, by total solar and infrared solar reflectance in the UV, visible, and infrared wavelength range, and by heat reflection. Among the coatings developed, two produced very effective controls for infrared reflectance and transparency, and they could control heat reflectance, resulting in a significant decrease in surface temperature.
Bell-State-Exchange-Parity-Based Protocol for Efficient Autocompensation of Quantum Key Distribution Encoded in Polarization or Spatial Modes
Authors: Carral Gabriel M. , Liñares Jesús , Mateo Eduardo F. , Prieto-Blanco Xesús
Published: December 2023

We analyze autocompensation possibilities in entanglement-based QKD protocols. In particular, we study the seminal BBM92 protocol and find that an autocompensating technique is possible, although with severe limitations. This prompts the introduction of a different, more practical protocol based on Bell state exchange parity (BSEP), which allows for intrinsic autocompensation of optical fiber perturbations in various two-dimensional fiber-optic encodings while retaining advantageous MDI-QKD characteristics. We present the BSEP protocol in detail, describing both the quantum light propagation and the optical hardware requirements. Finally, we analyze its security, computing its expected performance through the key rate.
An Order-Theoretic Study on Formal Concept Analysis
Authors: Syau Yu-Ru , Lin En-Bing , Liau Churn-Jung
Published: December 2023

This paper employs an order-theoretic framework to explore the intricacies of formal concepts. Initially, we establish a natural correspondence among formal contexts, preorders, and the resulting partially ordered sets (posets). Leveraging this foundation, we provide insightful characterizations of atoms and coatoms within finite concept lattices, drawing upon object intents. Expanding from the induced poset originating from a formal context, we extend these characterizations to discern join-irreducible and meet-irreducible elements within finite concept lattices. Contrary to a longstanding misunderstanding, our analysis reveals that not all object and attribute concepts are irreducible. This revelation challenges the conventional belief that rough approximations, grounded in irreducible concepts, offer sufficient coverage. Motivated by this realization, the paper introduces a novel concept: rough conceptual approximations. Unlike the conventional definition of object equivalence classes in Pawlakian approximation spaces, we redefine them by tapping into the extent of an object concept. Demonstrating their equivalence, we establish that rough conceptual approximations align seamlessly with approximation operators in the generalized approximation space associated with the preorder corresponding to a formal context. To illustrate the practical implications of these theoretical findings, we present concrete examples. Furthermore, we delve into the significance and potential applications of our proposed rough conceptual approximations, shedding light on their utility in real-world scenarios.
Risky Alcohol Consumption in the Elderly: Screening and Brief Intervention from Primary Care. The ALANE Study, a Randomized Clinical Trial
Authors: Torán Pere , Montesinos Susanna , Pachón-Camacho Alba , Diez-Fadrique Galadriel , Ruiz-Rojano Irene , Arteaga Ingrid , Pera Guillem , Montellà-Jordana Núria , Montero-Alía Pilar , Rodríguez-Pérez Carmina , Caballeria Llorenç , Chacón Carla
Published: December 2023

Background: Risky alcohol consumption (RAC) can lead to alcohol-related liver disease (ALD). Liver cirrhosis caused by ALD continues to increase as alcohol consumption continues unabated. In turn, the elderly are more sensitive to alcohol. Population ageing calls for preventive activities to improve their health. Brief interventions have proven to be cost-effective in addressing risk behaviours. Aim: We aimed to analyse the prevalence of RAC in people > 64 years and to assess the effect of a brief intervention in the subgroup of risky consumers. Methods: population-based study in two phases: (1) Phase I: Cross-sectional, descriptive multicentre study of prevalence of RAC in people > 64 years. (2) Phase II: Cluster randomized, controlled, single-blind, community-based clinical trial with two comparison groups of subjects with RAC, to assess the effectiveness of a brief intervention compared to standard practice in reducing alcohol consumption in primary care. Results: Out of the 932 subjects, 455 (49%) (268 men (64%) and 187 women (36%)) had an alcohol consumption that was considered to be risky. Overall, the brief intervention was effective in reducing alcohol consumption showing 1.8 OR (p = 0.030). That effect was caused by women whose group showed 3.3 OR (p = 0.009). There was no effect on men (p = 0.468). Conclusions: RAC in the elderly is very high, far more in men than in women. A brief intervention was successful in reducing alcohol consumption but not below risk levels. Further research is needed to determine which types of interventions are most effective in this population subgroup.
Periodontitis and Metabolic Syndrome: Statistical and Machine Learning Analytics of a Nationwide Study
Authors: Wilensky Asaf , Frank Noa , Mizraji Gabriel , Tzur Dorit , Goldstein Chen , Almoznino Galit
Published: December 2023

This study aimed to analyze the associations between periodontitis and metabolic syndrome (MetS) components and related conditions while controlling for sociodemographics, health behaviors, and caries levels among young and middle-aged adults. We analyzed data from the Dental, Oral, and Medical Epidemiological (DOME) record-based cross-sectional study that combines comprehensive sociodemographic, medical, and dental databases of a nationally representative sample of military personnel. The research consisted of 57,496 records of patients, and the prevalence of periodontitis was 9.79% (5630/57,496). The following parameters retained a significant positive association with subsequent periodontitis multivariate analysis (from the highest to the lowest OR (odds ratio)): brushing teeth (OR = 2.985 (2.739–3.257)), obstructive sleep apnea (OSA) (OR = 2.188 (1.545–3.105)), cariogenic diet consumption (OR = 1.652 (1.536–1.776)), non-alcoholic fatty liver disease (NAFLD) (OR = 1.483 (1.171–1.879)), smoking (OR = 1.176 (1.047–1.322)), and age (OR = 1.040 (1.035–1.046)). The following parameters retained a significant negative association (protective effect) with periodontitis in the multivariate analysis (from the highest to the lowest OR): the mean number of decayed teeth (OR = 0.980 (0.970–0.991)); North America as the birth country compared to native Israelis (OR = 0.775 (0.608–0.988)); urban non-Jewish (OR = 0.442 (0.280–0.698)); and urban Jewish (OR = 0.395 (0.251–0.620)) compared to the rural locality of residence. Feature importance analysis using the eXtreme Gradient Boosting (XGBoost) machine learning algorithm with periodontitis as the target variable ranked obesity, OSA, and NAFLD as the most important systemic conditions in the model. We identified a profile of the “patient vulnerable to periodontitis” characterized by older age, rural residency, smoking, brushing teeth, cariogenic diet, comorbidities of obesity, OSA and NAFLD, and fewer untreated decayed teeth. North American-born individuals had a lower prevalence of periodontitis than native Israelis. This study emphasizes the holistic view of the MetS cluster and explores less-investigated MetS-related conditions in the context of periodontitis. A comprehensive assessment of disease risk factors is crucial to target high-risk populations for periodontitis and MetS.
Exosomes: New Insights into the Pathogenesis of Metabolic Syndrome
Authors: Wang Ning , Li Jing , Hu Zixuan , Ngowi Ebenezeri Erasto , Yan Baolong , Qiao Aijun
Published: December 2023

Exosomes are a subtype of extracellular vesicles (EVs) with a diameter of 30~150 nm (averaging ~100 nm) that are primarily produced through the endosomal pathway, and carry various components such as lipids, proteins, RNA, and other small molecular substances. Exosomes can mediate intercellular communication through the bioactive substances they carry, thus participating in different physiological activities. Metabolic syndrome (MS) is a disease caused by disturbances in the body’s metabolism, mainly including insulin resistance (IR), diabetes, obesity, non-alcoholic fatty liver disease (NAFLD), hyperlipidemia, and atherosclerosis (AS). Recent studies have shown that exosomes are closely related to the occurrence and development of MS. Exosomes can act as messengers to mediate signaling transductions between metabolic cells in the organism and play a bidirectional regulatory role in the MS process. This paper mainly reviews the components, biogenesis, biological functions and potential applications of exosomes, and exosomes involved in the pathogenesis of MS as well as their clinical significance in MS diagnosis.
Alteration of Average Thickness of Lipid Bilayer by Membrane-Deforming Inclusions
Authors: Kondrashov Oleg V. , Akimov Sergey A.
Published: December 2023

Thickness of lipid bilayer membranes is a key physical parameter determining membrane permeability and stability with respect to formation of through pores. Most membrane inclusions or impurities like amphipathic peptides, transmembrane peptides, lipid inclusions of a different molecular shape, lipid domains, and protein-lipid domains, locally deform the membrane. The detailed structure of the locally deformed region of the membrane is a kind of “fingerprint” for the inclusion type. However, most experimental methods allow determining only averaged parameters of membranes with incorporated inclusions, thus preventing the direct obtaining of the characteristics of the inclusion. Here we developed a model that allows the obtaining of characteristic parameters of three types of membrane inclusions (amphipathic peptides, transmembrane peptides, monolayer lipid patches) from experimentally observable dependencies of the average thickness of lipid bilayer on the surface concentration of the inclusions. In the case of amphipathic peptides, the model provided the peptide parameters that were in qualitative agreement with the available experimental data.
Protective Effect of Topiramate against Diabetic Retinopathy and Computational Approach Recognizing the Role of NLRP3/IL-1β/TNF-α Signaling
Authors: Mohammad Hala M. F. , Eladl Mohamed Ahmed , Abdelmaogood Asmaa K. K. , Elshaer Rabie E. , Ghanam Walaa , Elaskary Abdelhakeem , Saleh Mohamed A. K. , Eltrawy Amira H. , Ali Sahar K. , Moursi Suzan M. M. , Bilasy Shymaa E. , Zaitone Sawsan A. , Alzlaiq Wafa Ali , Atteya Hayam
Published: December 2023

The possible impact of topiramate against diabetic retinopathy (DREN) and its molecular mechanisms in relation to the nod-like receptor family pyrin domain containing 3 (NLRP3) inflammasome has not been studied before. Thus, in the present study, we aimed to utilize a computational approach to investigate the possible protective effect of topiramate on experimental DREN and explore its impact on NLRP3/interlukin-1β signaling and brain-derived neurotrophic factor (BDNF) expression. Male albino mice were distributed to four experimental groups and assigned the following categorizations: (i) saline, (ii) diabetic, (iii) diabetic + topiramate 10 mg/kg and (iv) diabetic + topiramate 30 mg/kg. We observed shrinkage of total retinal thickness and elevation in retinal glutamate, malondialdehyde, NLRP3 and interlukin-1β but decreased glutathione (GSH) levels in the diabetic mice. Additionally, retinal ultra-structures in the diabetic group showed abnormalities and vacuolations in the pigmented epithelium, the photoreceptor segment, the outer nuclear layer, the inner nuclear layer and the ganglion cell layer (GCL). Mice treated with topiramate 10 or 30 mg/kg showed downregulation in retinal malondialdehyde, NLRP3 and interlukin-1β levels; improvements in the retinal pathologies; enhanced immunostaining for BDNF and improved ultra-structures in different retinal layers. Overall, the current results suggest topiramate as a neuroprotective agent for DREN, and future studies are warranted to further elucidate the mechanism of its protective action.
Synergy of Muscle and Cortical Activation through Vojta Reflex Locomotion Therapy in Young Healthy Adults: A Pilot Randomized Controlled Trial
Authors: Sánchez-González Juan Luis , Díez-Villoria Emiliano , Pérez-Robledo Fátima , Sanz-Esteban Ismael , Llamas-Ramos Inés , Llamas-Ramos Rocío , de la Fuente Antonio , Bermejo-Gil Beatriz María , Canal-Bedia Ricardo , Martín-Nogueras Ana María
Published: December 2023

Background: Vojta Therapy is a neurorehabilitation therapy that allows to activate reflex movement patterns. The scientific literature has shown its ability to generate muscle contractions. The activation of brain neural networks has also been proven. However, the relationship between these processes has not yet been demonstrated. For this reason, the aim of this study is to verify brain activation produced by recording with near-infrared spectroscopy and its relationship with muscle activation produced in the abdominal muscles recorded with surface electromyography. Methods: A total sample of 27 healthy subjects over 18 years of age was recruited. An experimental study on a cohort was conducted. Two experimental conditions were considered: stimuli according to the Vojta protocol, and a control non-stimuli condition. Abdominal muscle activation was measured using surface electromyography, and the activation of the motor cortex was assessed with near-infrared spectroscopy. Results: In relation to the oxygenated hemoglobin concentration (HbO), an interaction between the stimulation phase and group was observed. Specifically, the Vojta stimulation group exhibited an increase in concentration from the baseline phase to the first resting period in the right hemisphere, contralateral to the stimulation area. This rise coincided with an enhanced wavelet coherence between the HbO concentration and the electromyography (EMG) signal within a gamma frequency band (very low frequency) during the first resting period. Conclusions: The results underscore the neurophysiological effects on the brain following tactile stimulation via Vojta Therapy, highlighting increased activity in pivotal areas essential for sensory processing, motor planning, and control. This activation, particularly evident in the Vojta stimulation group, aligns with previous findings, suggesting that tactile stimuli can not only evoke the intention to move but can also initiate actual muscle contractions, emphasizing the therapy’s potential in enhancing innate locomotion and rolling movements in patients with neurological disorders.
Evolutionary Computing for the Radiative–Convective Heat Transfer of a Wetted Wavy Fin Using a Genetic Algorithm-Based Neural Network
Authors: Poornima B. S. , Sarris Ioannis E. , Chandan K. , Nagaraja K.V. , Kumar R. S. Varun , Ben Ahmed Samia
Published: December 2023

Evolutionary algorithms are a large class of optimization techniques inspired by the ideas of natural selection, and can be employed to address challenging problems. These algorithms iteratively evolve populations using crossover, which combines genetic information from two parent solutions, and mutation, which adds random changes. This iterative process tends to produce effective solutions. Inspired by this, the current study presents the results of thermal variation on the surface of a wetted wavy fin using a genetic algorithm in the context of parameter estimation for artificial neural network models. The physical features of convective and radiative heat transfer during wet surface conditions are also considered to develop the model. The highly nonlinear governing ordinary differential equation of the proposed fin problem is transmuted into a dimensionless equation. The graphical outcomes of the aspects of the thermal profile are demonstrated for specific non-dimensional variables. The primary observation of the current study is a decrease in temperature profile with a rise in wet parameters and convective-conductive parameters. The implemented genetic algorithm offers a powerful optimization technique that can effectively tune the parameters of the artificial neural network, leading to an enhanced predictive accuracy and convergence with the numerically obtained solution.
Sine Cosine Algorithm for Elite Individual Collaborative Search and Its Application in Mechanical Optimization Designs
Authors: Tang Junjie , Wang Lianguo
Published: December 2023

To address the shortcomings of the sine cosine algorithm such as the low search accuracy, slow convergence speed, and easily falling into local optimality, a sine cosine algorithm for elite individual collaborative search was proposed. Firstly, tent chaotic mapping was used to initialize the population and the hyperbolic tangent function was applied non-linearly to adjust the parameters of the sine cosine algorithm, which enhanced the uniformity of population distribution and balanced the global exploration and local exploitation ability. Secondly, the search method of the sine cosine algorithm was improved by combining the search strategy of the sine cosine algorithm, the m-neighborhood locally optimal individual-guided search strategy, and the global optimal individual-guided search strategy, and, then, the three search strategies were executed alternately, which achieved collaboration, improved the convergence accuracy, and prevented the algorithm from falling into local optima. Finally, a greedy selection strategy was employed to select the best individuals for the population, which accelerated the convergence speed of the sine cosine algorithm. The simulation results illustrated that the sine cosine algorithm for elite individual collaborative search demonstrated a better optimization performance than the sine cosine algorithm, the other improved sine cosine algorithms, the other chaos-based algorithms, and other intelligent optimization algorithms. In addition, the feasibility and applicability of the sine cosine algorithm for elite individual collaborative search were further demonstrated by two mechanical optimization design experiments.
Anti-Fibronectin Aptamer Modifies Blood Clot Pattern and Stimulates Osteogenesis: An Ex Vivo Study
Authors: da Costa Natacha Malu Miranda , Parisi Ludovica , Ghezzi Benedetta , Elviri Lisa , de Souza Sergio Luis Scombatti , Novaes Arthur Belém , de Oliveira Paulo Tambasco , Macaluso Guido Maria , Palioto Daniela Bazan
Published: December 2023

Background: Scaffold (SCA) functionalization with aptamers (APT) provides adsorption of specific bioactive molecules on biomaterial surfaces. The aim of this study was to observe if SCA enriched with anti-fibronectin APT can favor coagulum (PhC) and osteoblasts (OSB) differentiation. Methods: 20 μg of APT was functionalized on SCA by simple adsorption. For PhC formation, SCAs were inserted into rat calvaria defects for 17 h. Following proper transportation (buffer solution PB), OSBs (UMR-106 lineage) were seeded over PhC + SCAs with and without APT. Cells and PhC morphology, PhC cell population, protein labeling and gene expression were observed in different time points. Results: The APT induced higher alkaline phosphatase and bone sialoprotein immunolabeling in OSB. Mesenchymal stem cells, leukocytes and lymphocytes cells were detected more in the APT group than when scaffolds were not functionalized. Additionally, an enriched and dense fibrin network and different cell types were observed, with more OSB and white blood cells in PhC formed on SCA with APT. The gene expression showed higher transforming growth factor beta 1 (TGF-b1) detection in SCA with APT. Conclusions: The SCA functionalization with fibronectin aptamers may alter key morphological and functional features of blood clot formation, and provides a selective expression of proteins related to osteo differentiation. Additionally, aptamers increase TGF-b1 gene expression, which is highly associated with improvements in regenerative therapies.
Risk Factors for Radiation Necrosis and Local Recurrence after Proton Beam Therapy for Skull Base Chordoma or Chondrosarcoma
Authors: Takahashi Mizuki , Mizumoto Masashi , Oshiro Yoshiko , Kino Hiroyoshi , Akutsu Hiroyoshi , Nakai Kei , Sumiya Taisuke , Ishikawa Eiichi , Maruo Kazushi , Sakurai Hideyuki
Published: December 2023

[Proposal] Here, we retrospectively evaluate risk factors for radiation necrosis and local recurrence after PBT for skull base chordoma or chondrosarcoma. [Patients and Methods] We analyzed 101 patients who received PBT for skull base chordomas and chondrosarcomas from January 1989 to February 2021. Multivariable logistic regression models were applied for local recurrence, temporal lobe radiation necrosis rates, and temporal lobe radiation necrosis. [Results] In multivariate analysis, chordoma and large tumor size were independent significant factors for local recurrence. The 1-, 2-, 3-, 4- and 5-year local recurrence rates were 3.9%, 16.9%, 20.3%, 28.5% and 44.0% for chordoma and 0%, 0%, 0%, 0% and 7.1% for chondrosarcoma, respectively. The local recurrence rates of small tumors (<30 mm) were 4.3%, 14.7%, 17.7%, 17.7% and 25.9%, and those for large tumors were 3.6%, 15.1%, 19.2%, 32.7% and 59.6%, respectively. In multivariate analysis, BED Gy10 and total dose were risk factors for radiation necrosis. [Conclusions] For skull base chordoma and chondrosarcoma, the risk factors of local recurrence were chordoma and large tumor size, and those of radiation necrosis were BED Gy10 and total dose, respectively. DVH analysis is needed to investigate the risk factors for brain necrosis in more detail.
Metronomic Temozolomide (mTMZ) and Bevacizumab—The Safe and Effective Frontier for Treating Metastatic Neuroendocrine Tumors (NETs): A Single-Center Experience
Authors: Ünal Çağlar , Sağlam Sezer
Published: December 2023

Addressing the persistent challenges in treating metastatic neuroendocrine tumors (NETs) demands ongoing refinement and innovation in therapeutic strategies. This study investigates the potential advantages of combining metronomic temozolomide (mTMZ) with bevacizumab for patients diagnosed with metastatic NETs, particularly focusing on those with a Ki-67 index under 55%. Data from 30 patients were analyzed, using key performance indicators such as progression-free survival (PFS), overall survival (OS), and response rates to therapy, to gauge the treatment’s efficacy. The results were encouraging: the median PFS recorded was 16.3 months, and the OS was 25.9 months. The disease control rate (DCR) reached an impressive 86.7%, and the objective response rate (ORR) stood at 63.3%. The treatment regimen was well-tolerated, with no reported instances of grade 4 toxicities. Such a safety profile indicates that this regimen may be particularly advantageous for older, fragile patients who might struggle with conventional dosage levels. These initial findings suggest that the mTMZ and bevacizumab combination could potentially rival the conventional temozolomide–capecitabine therapy in managing metastatic NETs. We aimed to meticulously assess the efficacy of the mTMZ and bevacizumab combination in treating metastatic NETs. Given the initial promising results, a more conclusive understanding of its efficacy will require further research through larger, multicenter prospective clinical trials.
AhR, PXR and CAR: From Xenobiotic Receptors to Metabolic Sensors
Authors: Rakateli Leonida , Huchzermeier Rosanna , van der Vorst Emiel P. C.
Published: December 2023

Traditionally, xenobiotic receptors are known for their role in chemical sensing and detoxification, as receptor activation regulates the expression of various key enzymes and receptors. However, recent studies have highlighted that xenobiotic receptors also play a key role in the regulation of lipid metabolism and therefore function also as metabolic sensors. Since dyslipidemia is a major risk factor for various cardiometabolic diseases, like atherosclerosis and non-alcoholic fatty liver disease, it is of major importance to understand the molecular mechanisms that are regulated by xenobiotic receptors. In this review, three major xenobiotic receptors will be discussed, being the aryl hydrocarbon receptor (AhR), pregnane X receptor (PXR) and the constitutive androstane receptor (CAR). Specifically, this review will focus on recent insights into the metabolic functions of these receptors, especially in the field of lipid metabolism and the associated dyslipidemia.
Swift Removal of the Heavy Metals Cadmium and Lead from an Aqueous Solution by a CAN-Zeolite Synthesized from Natural Clay
Authors: Aloui Lobna , Mezghich Soumaya , Mansour Lamjed , Hraiech Sana , Ayari Fadhila
Published: December 2023

CAN-zeolite was synthesized with a high purity from natural kaolinite via alkali fusion by hydrothermal treatment at a pressure of 1 kbar H2O. It was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), infrared spectroscopy and nitrogen adsorption at 77 K. The results show that after AK hydrothermal treatment (under specific conditions), the SBET increases from 5.8 m2g−1 to 30.07 m2g−1 which is six times greater. The AK which was a non-porous or macroporous solid (the nitrogen adsorption/desorption of AK is of type II) became mesoporous (N2 adsorption–desorption isotherms exhibit typical hysteresis of type IV) with a pore size of 5.9 Å. XRD of AK shows the presence of quartz (Q) as impurities, and illite and kaolinite as major fractions; after hydrothermal treatment, the XRD diffractogram shows only fine pics related to CAN-zeolite (with a good crystallinity), confirming the success of the synthesized process. These results suggest that the synthesized CAN-zeolite has the potential to be tested in the removal of heavy metals from waste water as part of a remediation process. Batch reactors were used to evaluate the adsorption isotherms and kinetic studies of heavy metals, cadmium, and lead, by natural kaolinite clay (AK) and synthesized cancrinite zeolite (CAN-zeolite). The results show that the adsorption kinetics of the bivalent heavy metals cadmium and lead are extremely fast with either AK or CAN-zeolite. Equilibrium was reached within 2 min. Adsorption isotherms show that the synthesized CAN-zeolite has a higher adsorption capacity; the retention capacity of lead and cadmium was three times greater than that presented by the natural clay mineral. According to the findings, CAN-zeolite has a higher affinity for PbII (192 mg/g) compared to CdII (68 mg/g). The negative reactive surface sites interacting with these cationic heavy metals resulted in a higher amount of heavy metals adsorption than the cation exchange capacity (CEC). The adsorption information was analyzed using the Langmuir and Freundlich equations. The Langmuir model provided a good fit to the equilibrium data, indicating a monolayer adsorption mechanism.
Addressing a Growing Crisis: Exploring Novel Insights and Solutions in Research on Nutrition and Childhood and Adolescent Obesity
Authors: Foscolou Alexandra , Androutsos Odysseas , Kosti Rena I.
Published: December 2023

Given the escalating global prevalence of non-communicable diseases (NCDs), it is consequently crucial to address childhood obesity by promoting lifestyle adjustments, as exemplified in the World Health Organization’s Package of Essential Non-Communicable Disease Interventions for Primary Healthcare [...]
From Scribbles to Script: Graphomotor Skills’ Impact on Spelling in Early Primary School
Authors: Maurer Michelle N. , Truxius Lidia , Sägesser Wyss Judith , Eckhart Michael
Published: December 2023

The acquisition of handwriting skills is a crucial goal in early primary school. Yet our comprehension of handwriting development, encompassing graphomotor skills and spelling, remains fragmented. The identification of predictors for handwriting skills is essential for providing early support. This longitudinal study aimed to explore the predictive roles of gender, working memory, and motivation to handwrite for graphomotor skills six months later and spelling skills one year later. Paper-and-pencil tasks (graphomotor skills, spelling), a tablet task (working memory), and a questionnaire (teachers’ ratings of children’s handwriting motivation) were employed. This study included 363 first-grade children (49.8% girls) aged 6–9 years. Results from a structural equation model, controlling for age and socioeconomic background, revealed that girls exhibited superior performance in graphomotor skills, while boys tended to spell more accurately. Furthermore, working memory predicted graphomotor skills but not spelling. Additionally, motivation to handwrite predicted both first-grade graphomotor skills and second-grade spelling. This study extends contemporary evidence, demonstrating that graphomotor skills predict spelling while considering gender and motivation. The findings underscore the pivotal role of graphomotor skills in spelling acquisition and suggest their contribution to spelling difficulties.
Anti-Obesity Effect of Daidzein Derived from Pachyrhizus erosus (L.) Urb. Extract via PPAR Pathway in MDI-Induced 3T3-L1 Cell Line
Authors: Choi Moon-Hee , Yang Seung-Hwa , Lee Yeo-Jin , Sohn Jeong Ho , Lee Ki Sun , Shin Hyun-Jae
Published: December 2023

Pachyrhizus erosus (L.) Urb. is a tropical perennial vine plant native to southern Mexico, Southeast Asia, Central America, and Africa. In this study, we analyzed and identified various polyphenolic compounds and isoflavones present in ethanolic P. erosus root extracts and investigated their potential anti-obesity activity as a natural health food resource. The extraction process involved drying the yam bean, followed by extraction with 70% ethanol, evaporation, and freeze-drying. Fractionation was achieved through layer separation using n-hexane, ethyl acetate (EtOAc), butanol (BuOH), and water. The EtOAc fraction exhibited the highest antioxidant activity among the experimental groups, with an IC50 value of 531.77 µg/mL for ABTS radical scavenging. In α-glucosidase and lipase inhibition assays, IC50 values were determined to be 873.07 µg/mL and 915.02 µg/mL, respectively. Using HPLC and LC-MS/MS, we detected isoflavone components in P. erosus root extracts, identifying daidzein, genistein, and rotenone among them. Daidzein was the most abundant isoflavone in P. erosus root extracts. To validate the anti-obesity activity in the EtOAc fraction and daidzein, we used 3T3-L1 preadipocytes treated with MDI (3-isobutyl-1-methylxanthine, dexamethasone, insulin) for 8 days. Oil Red O staining experiments demonstrated a concentration-dependent reduction in lipid content in the EtOAc fraction and daidzein treatment groups. Additionally, we examined the expression pattern of proteins related to the leptin-PPAR-FAS Pathway, revealing a concentration-dependent decrease in obesity-related proteins.
Long-Term Follow-Up of Tamoxifen Treatment and the Use of Imaging in Psammocarcinoma: A Case Report, Review of the Literature and Discussion of Diagnostic and Therapeutic Challenges
Authors: Gideonsson Ida , Israelsson Pernilla , Strandberg Sara N. , Ottander Ulrika
Published: December 2023

Psammocarcinoma (PsC) represents a rare form of low-grade serous tumor of the ovary or peritoneum. Although ovarian cancer generally has a poor prognosis in its late stages, PsC seems to have a more indolent course. We present a patient with a history of unspecific abdominal pain for more than a year, with sudden acute onset of severe inguinal pain. On admission to the hospital, a computed tomography (CT) revealed a pelvic mass of suspected ovarian origin. Radical surgery was attempted but not achieved due to widespread tumor growth. Histopathological evaluation revealed estrogen receptor-positive stage III PsC. Tamoxifen treatment was thus initiated, still maintaining stable disease 10 years later. The patient has undergone extensive radiological work-up, including CT, chest X-ray, 18F-fluoro-deoxy-glucose positron emission tomography (PET)/CT, 99mTc- hydroxymethylene diphosphonate (HDP) bone scintigraphy, 18F-fluoro-thymidine (FLT) PET/CT, Tc-99m depreotide scintigraphy and magnetic resonance imaging. In conclusion, we demonstrate that PsC has characteristic radiological features and different imaging modalities can be suitable in different clinical situations. In contrast to most other ovarian cancers, PsC does not always warrant adjuvant chemotherapy, even in advanced stages. This emphasizes the need for a deeper knowledge of the biological behavior of this rare tumor, to select the optimal treatment strategy.
Incorporating Stereotactic Ablative Radiotherapy into the Multidisciplinary Management of Renal Cell Carcinoma
Authors: Raj Rohit K. , Upadhyay Rituraj , Wang Shang-Jui , Singer Eric A. , Dason Shawn
Published: December 2023

Stereotactic ablative radiotherapy (SABR) has challenged the conventional wisdom surrounding the radioresistance of renal cell carcinoma (RCC). In the past decade, there has been a significant accumulation of clinical data to support the safety and efficacy of SABR in RCC. Herein, we review the use of SABR across the spectrum of RCC. We performed an online search of the Pubmed database from January 1990 through April 2023. Studies of SABR/stereotactic radiosurgery targeting primary, extracranial, and intracranial metastatic RCC were included. For SABR in non-metastatic RCC, this includes its use in small renal masses, larger renal masses, and inferior vena cava tumor thrombi. In the metastatic setting, SABR can be used at diagnosis, for oligometastatic and oligoprogressive disease, and for symptomatic reasons. Notably, SABR can be used for both the primary renal tumor and metastasis-directed therapy. Management of RCC is evolving rapidly, and the role that SABR will have in this landscape is being assessed in a number of ongoing prospective clinical trials. The objective of this narrative review is to summarize the evidence corroborating the use of SABR in RCC.