bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative Bonding Analysis of Computer-Aided Design/Computer-Aided Manufacturing Dental Resin Composites with Various Resin Cements
Authors: Komagata Yuya , Nagamatsu Yuki , Ikeda Hiroshi
Published: October 2023

The use of dental resin composites adapted to computer-aided design/computer-aided manufacturing (CAD/CAM) processes for indirect tooth restoration has increased. A key factor for a successful tooth restoration is the bond between the CAD/CAM composite crown and abutment tooth, achieved using resin-based cement. However, the optimal pairing of the resin cement and CAD/CAM composites remains unclear. This study aimed to identify the optimal combination of a CAD/CAM composite and resin cement for bonding. A commercial methyl methacrylate (MMA)-based resin cement (Super-Bond (SB)) and four other composite-based resin cements (PANAVIA V5; PV, Multilink Automix (MA), ResiCem EX (RC), and RelyX Universal Resin Cement (RX)) were tested experimentally. For the CAD/CAM composites, a commercial polymer-infiltrated ceramic network (PICN)-based composite (VITA ENAMIC (VE)) and two dispersed filler (DF)-based composites (SHOFU BLOCK HC (SH) and CERASMART300 (CE)) were used. Each composite block underwent cutting, polishing, and alumina sandblasting. This was followed by characterization using scanning electron microscopy, inorganic content measurement, surface free energy (SFE) analysis, and shear bond strength (SBS) testing. The results demonstrated that the inorganic content and total SFE of the VE composite were the highest among the examined composites. Furthermore, it bonded highly effectively to all the resin cements. This indicated that PICN-based composites exhibit unique bonding features with resin cements. Additionally, the SBS test results indicated that MMA-based resin cement bonds effectively with both DF- and PICN-based composites. The combination of the PICN-based composite and MMA-based resin cement showed the best bonding performance.
Machine Learning-Based Fatigue Life Prediction of Functionally Graded Materials Using Material Extrusion Technology
Authors: Alkunte Suhas , Fidan Ismail
Published: October 2023

In this study, the research investigates the prediction of fatigue life for Functionally Graded Materials (FGM) specimens comprising Polylactic acid (PLA) and Thermoplastic Polyurethane (TPU). For this, Machine learning (ML) techniques, including Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN) are utilized. A predictive in-house code is developed for each technique, thereby facilitating the fatigue performance of layered deposited specimens subjected to varying cyclic loadings. In order to verify the effectiveness of the ML technique, a comparative analysis among all is reported based on empirically determined fatigue life obtained values. RF is proven to be the most suitable technique with minimal error percentage in obtained results with optimally synchronized data sets in a minimum time frame. Subsequently, the application of ML in those predictions is reported for future aspects in augmenting the operational efficiency associated with fatigue life prediction.
Black Phosphorus-Based ZnO-Ag Nanocomposite for Antibacterial Activity against Tigecycline-Resistant Acinetobacter baumannii
Authors: Naskar Atanu , Cho Hyejin , Kim Kwang-sun
Published: October 2023

Acinetobacter baumannii is a critically hard-to-treat gram-negative pathogen responsible for a range of infectious diseases. Tigecycline is a last-resort antibiotic for A. baumannii infection; however, tigecycline-resistant (TIG-R) A. baumannii has been increasingly reported. Therefore, new strategies must be developed to treat these detrimental infections. Nanoantibiotics composed of two-dimensional (2D) black phosphorus (BP) and its derived nanocomposites have emerged as excellent alternatives to current antibiotics. However, the development of unique materials to target specific pathogens is challenging. Here, we report the preparation of a BP-based ZnO-Ag (ZPBA) nanocomposite. A low-temperature solution synthesis method was used to prepare ZnO and Ag nanoparticles immobilized on BP nanosheets. X-ray diffraction, transmission electron microscopy, and X-ray photoelectron spectroscopy were used to characterize the ZPBA nanocomposite. The antibacterial activity of ZPBA nanocomposite was assessed by determining its minimum inhibitory concentration against type (ATCC 19606, ATCC 15150) and TIG-R (ATCC 19606-R) A. baumannii strains. From the assays, ZPBA showed superior activity against TIG-R A. baumannii strain with MIC of 12.5 µg·mL−1 compared to all other prepared samples. Finally, the combination of bacterial membrane disruption and ROS generation was demonstrated to be a potential antibacterial mechanism of ZPBA. Our results show that ZPBA could be a potential nanoantibiotic platform for eradicating TIG-R A. baumannii.
The Porosity Design and Deformation Behavior Analysis of Additively Manufactured Bone Scaffolds through Finite Element Modelling and Mechanical Property Investigations
Authors: Rasheed Shummaila , Lughmani Waqas Akbar , Khan Muhammad Mahabat , Brabazon Dermot , Obeidi Muhannad Ahmed , Ahad Inam Ul
Published: October 2023

Additively manufactured synthetic bone scaffolds have emerged as promising candidates for the replacement and regeneration of damaged and diseased bones. By employing optimal pore architecture, including pore morphology, sizes, and porosities, 3D-printed scaffolds can closely mimic the mechanical properties of natural bone and withstand external loads. This study aims to investigate the deformation pattern exhibited by polymeric bone scaffolds fabricated using the PolyJet (PJ) 3D printing technique. Cubic and hexagonal closed-packed uniform scaffolds with porosities of 30%, 50%, and 70% are utilized in finite element (FE) models. The crushable foam plasticity model is employed to analyze the scaffolds’ mechanical response under quasi-static compression. Experimental validation of the FE results demonstrates a favorable agreement, with an average percentage error of 12.27% ± 7.1%. Moreover, the yield strength and elastic modulus of the scaffolds are evaluated and compared, revealing notable differences between cubic and hexagonal closed-packed designs. The 30%, 50%, and 70% porous cubic pore-shaped bone scaffolds exhibit significantly higher yield strengths of 46.89%, 58.29%, and 66.09%, respectively, compared to the hexagonal closed-packed bone scaffolds at percentage strains of 5%, 6%, and 7%. Similarly, the elastic modulus of the 30%, 50%, and 70% porous cubic pore-shaped bone scaffolds is 42.68%, 59.70%, and 58.18% higher, respectively, than the hexagonal closed-packed bone scaffolds at the same percentage strain levels. Furthermore, it is observed in comparison with our previous study the μSLA-printed bone scaffolds demonstrate 1.5 times higher elastic moduli and yield strengths compared to the PJ-printed bone scaffolds.
Musculoskeletal Biomaterials: Stimulated and Synergized with Low Intensity Pulsed Ultrasound
Authors: Jia Wanru , Zhou Zifei , Zhan Weiwei
Published: October 2023

Clinical biophysical stimulating strategies, which have significant effects on improving the function of organs or treating diseases by causing the salutary response of body, have shown many advantages, such as non-invasiveness, few side effects, and controllable treatment process. As a critical technique for stimulation, the low intensity pulsed ultrasound (LIPUS) has been explored in regulating osteogenesis, which has presented great promise in bone repair by delivering a combined effect with biomaterials. This review summarizes the musculoskeletal biomaterials that can be synergized with LIPUS for enhanced biomedical application, including bone regeneration, spinal fusion, osteonecrosis/osteolysis, cartilage repair, and nerve regeneration. Different types of biomaterials are categorized for summary and evaluation. In each subtype, the verified biological mechanisms are listed in a table or graphs to prove how LIPUS was effective in improving musculoskeletal tissue regeneration. Meanwhile, the acoustic excitation parameters of LIPUS that were promising to be effective for further musculoskeletal tissue engineering are discussed, as well as their limitations and some perspectives for future research. Overall, coupled with biomimetic scaffolds and platforms, LIPUS may be a powerful therapeutic approach to accelerate musculoskeletal tissue repair and even in other regenerative medicine applications.
New Insights into Sea Turtle Propulsion and Their Cost of Transport Point to a Potential New Generation of High-Efficient Underwater Drones for Ocean Exploration
Authors: van der Geest Nick , Garcia Lorenzo , Nates Roy , Borrett Fraser
Published: October 2023

Sea turtles gracefully navigate their marine environments by flapping their pectoral flippers in an elegant routine to produce the required hydrodynamic forces required for locomotion. The propulsion of sea turtles has been shown to occur for approximately 30% of the limb beat, with the remaining 70% employing a drag-reducing glide. However, it is unknown how the sea turtle manipulates the flow during the propulsive stage. Answering this research question is a complicated process, especially when conducting laboratory tests on endangered animals, and the animal may not even swim with its regular routine while in a captive state. In this work, we take advantage of our robotic sea turtle, internally known as Cornelia, to offer the first insights into the flow features during the sea turtle’s propulsion cycle consisting of the downstroke and the sweep stroke. Comparing the flow features to the animal’s swim speed, flipper angle of attack, power consumption, thrust and lift production, we hypothesise how each of the flow features influences the animal’s propulsive efforts and cost of transport (COT). Our findings show that the sea turtle can produce extremely low COT values that point to the effectiveness of the sea turtle propulsive technique. Based on our findings, we extract valuable data that can potentially lead to turtle-inspired elements for high-efficiency underwater drones for long-term underwater missions.
Macro-TSH: An Uncommon Explanation for Persistent TSH Elevation That Thyroidologists Have to Keep in Mind
Authors: Chiardi Isabella , Rotondi Mario , Cantù Marco , Keller Franco , Trimboli Pierpaolo
Published: October 2023

A macro-thyroid-stimulating hormone (macro-TSH) is an infrequent yet noteworthy phenomenon in the thyroid field. A 69-year-old patient presented with persistently elevated thyroid-stimulating hormone (TSH) levels ranging from 30 to 50 mIU/L, paradoxically accompanied by normal thyroid hormone levels and normal thyroid ultrasound, with no findings on pituitary magnetic resonance. Laboratory studies were conducted to investigate potential interferences impacting the accuracy of TSH measurements. After excluding other potential causes, polyethylene glycol (PEG) precipitation technique was used, which led us to the diagnosis of macro-TSH. This result was confirmed through chromatography. Macro-TSH, although rare, emerged as the key contributor to the patient’s unexplained increase in TSH levels. This case highlights the importance of considering macro-TSH as a potential etiology in cases characterized by unexplained TSH elevation, offering insights into diagnostic protocols and expanding our understanding of thyroid function anomalies.
Gait Pattern in Charcot-Marie-Tooth Disease Type 1A According to Disease Severity
Authors: Park Jihyun , Joo So Young , Choi Byung-Ok , Kim Dae-Hyun , Park Jong Bum , Lee Jong Weon , Kim Deog Young
Published: October 2023

The aim of this study was to evaluate the characteristics of gait patterns in Charcot-Marie-Tooth disease type 1A (CMT1A) patients according to disease severity. Twenty-two CMT1A patients were enrolled and classified into two groups, according to the disease severity. The healthy control group consisted of 22 subjects with no gait impairment. Full barefoot three-dimensional gait analysis with temporospatial, kinematic, and kinetic data was performed among the mild and moderate CMT1A group and the control group. Minimal hip abduction, maximal hip extension generation, peak knee flexion moment at stance, ankle dorsiflexion at initial contact, maximal ankle plantarflexion at push-off and maximal ankle rotation moment at stance in the CMT1A group showed a significant difference compared to the control group (p < 0.05). In the moderate group, there were greater maximal hip flexion angles in swing, and smaller dorsiflexion angles at initial contact compared to the control group and mild group. CMT patients had typical gait characteristics and their gait patterns were different according to severity. The analysis of gait patterns in patients with CMT1A will help to understand gait function and provide important information for the treatment of patients with CMT in the future.
Sepsis and Clinical Simulation: What Is New? (and Old)
Authors: Cuesta-Montero Pablo , Navarro-Martínez Jose , Yedro Melina , Galiana-Ivars María
Published: October 2023

Background: Sepsis is a critical and potentially fatal condition affecting millions worldwide, necessitating early intervention for improved patient outcomes. In recent years, clinical simulation has emerged as a valuable tool for healthcare professionals to learn sepsis management skills and enhance them. Methods: This review aims to explore the use of clinical simulation in sepsis education and training, as well as its impact on how healthcare professionals acquire knowledge and skills. We conducted a thorough literature review to identify relevant studies, analyzing them to assess the effectiveness of simulation-based training, types of simulation methods employed, and their influence on patient outcomes. Results: Simulation-based training has proven effective in enhancing sepsis knowledge, skills, and confidence. Simulation modalities vary from low-fidelity exercises to high-fidelity patient simulations, conducted in diverse settings, including simulation centers, hospitals, and field environments. Importantly, simulation-based training has shown to improve patient outcomes, reducing mortality rates and hospital stays. Conclusion: In summary, clinical simulation is a powerful tool used for improving sepsis education and training, significantly impacting patient outcomes. This article emphasizes the importance of ongoing research in this field to further enhance patient care. The shift toward simulation-based training in healthcare provides a safe, controlled environment for professionals to acquire critical skills, fostering confidence and proficiency when caring for real sepsis patients.
The Role of Nodes and Nodal Assessment in Diagnosis, Treatment and Prediction in ER+, Node-Positive Breast Cancer
Authors: Kay Charlene , Martinez-Perez Carlos , Dixon J. Michael , Turnbull Arran K.
Published: October 2023

The majority of breast cancers are oestrogen receptor-positive (ER+). In ER+ cancers, oestrogen acts as a disease driver, so these tumours are likely to be susceptible to endocrine therapy (ET). ET works by blocking the hormone’s synthesis or effect. A significant number of patients diagnosed with breast cancer will have the spread of tumour cells into regional lymph nodes either at the time of diagnosis, or as a recurrence some years later. Patients with node-positive disease have a poorer prognosis and can respond less well to ET. The nodal metastases may be genomically similar or, as is becoming more evident, may differ from the primary tumour. However, nodal metastatic disease is often not assessed, and treatment decisions are almost always based on biomarkers evaluated in the primary tumour. This review will summarise the evidence in the field on ER+, node-positive breast cancer, including diagnosis, treatment, prognosis and predictive tools.
Exploring Protein Kinase CK2 Substrate Recognition and the Dynamic Response of Substrate Phosphorylation to Kinase Modulation
Authors: Cesaro Luca , Zuliani Angelica Maria , Bosello Travain Valentina , Salvi Mauro
Published: October 2023

Protein kinase CK2 (formerly known as casein kinase 2 or II), a ubiquitous and constitutively active enzyme, is widely recognized as one of the most pleiotropic serine/threonine kinases. It plays a critical role in numerous signaling pathways, with hundreds of bona fide substrates. However, despite considerable research efforts, our understanding of the entire CK2 substratome and its functional associations with the majority of these substrates is far from being completely deciphered. In this context, we aim to provide an overview of how CK2 recognizes its substrates. We will discuss the pros and cons of the existing methods to manipulate CK2 activity in cells, as well as exploring the dynamic response of substrate phosphorylation to CK2 modulation.
Quantification of Amu River Riverbank Erosion in Balkh Province of Afghanistan during 2004–2020
Authors: Mahmoodzada Abdul Basir , Varade Divyesh , Shimada Sawahiko , Okazawa Hiromu , Aryan Shafiqullah , Gulab Gulbuddin , Mustafa Abd El-Zaher M. A. , Rizwana Humaira , Ahlawat Yogesh K. , Elansary Hosam O.
Published: October 2023

In this study, we propose quantifying the Amu River riverbank erosion with the modelled river discharge in Kaldar District, Balkh Province of Afghanistan from 2004 to 2020. We propose a framework synergizing multi-source information for modelling the erosion area based on three components: (1) river discharge, (2) river width, and (3) erosion area. The total river discharge for the watershed shared by Afghanistan and Tajikistan was modelled using hydrological parameters from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) data through multivariate linear regression with ground station data. The river width was determined manually using the Normalized Difference Water Index (NDWI) derived from Landsat data. The riverbank erosion area was derived from the digital shoreline analysis using the NDWI. The digital shoreline analysis showed that, between 2008 and 2020, the average riverbank erosion area in Kaldar District is about 5.4 km2 per year, and, overall, 86.3 km2 during 2004–2020 due to flood events. The significantly higher land loss events occurred at 10 km2 bank erosion during the years 2008–2009 and 2015–2016, and 19 km2 peak erosion occurred during 2011–2012. A linear relation between the erosion area with respect to the discharge intensity and the specific stream power was observed with an R2 of 0.84 and RMSE of 1.761 for both.
Incorporation of Spatially Heterogeneous Area Partitioning into Vector-Based Cellular Automata for Simulating Urban Land-Use Changes
Authors: Zhu Jie , Zhu Mengyao , Na Jiaming , Lang Ziqi , Lu Yi , Yang Jing
Published: October 2023

In cellular automata (CA) modeling, spatial heterogeneity can be delineated by geographical area partitioning. The dual constrained space clustering method is a prevalent approach for providing an objective and effective representation of differences within urban regions. However, previous studies faced issues by ignoring spatial heterogeneity, which could lead to an over- or under-estimation of the simulation results. Accordingly, this study attempts to incorporate spatially heterogeneous area partitioning into vector-based cellular automata (VCA), producing more accurate and reliable simulations of urban land-use change. First, an area partition strategy with DSC algorithm was employed to generate multiple relatively homogeneous sub-regions, which can effectively capture the spatial heterogeneity in the distribution of land-use change factors. Second, UrbanVCA, a brand-new VCA-based framework, was utilized for simulating land-use changes in distinct urban partitions. Finally, the constructed partitioned VCA model was applied to simulate rapid urban development in Jiangyin city from 2012 to 2017. The results indicated that the combination of DSC clustering and UrbanVCA model could obtain satisfying results as the average FoM values for the partitions and the entire study area exceeded 0.22. Furthermore, a comparative analysis of results from traditional area-partitioned CA models revealed that the proposed area partitioning approach had the potential to yield more accurate simulation outcomes as the FoM values were higher and SHDI and LSI metrics were closer to real-world observations, indicating its good performance in simulating fragmented urban landscapes.
Effect of Different Tillage and Residue Management Options on Soil Water Transmission and Mechanical Behavior
Authors: Singh Vicky , Gupta Rajeev Kumar , Kahlon M. S. , Toor A. S. , Singh K. B. , Al-Ansari Nadhir , Mattar Mohamed A.
Published: October 2023

Understanding the variability in the mechanical and hydrological soil characteristics resulting from diverse tillage and residue management practices is essential for evaluating the adoption of conservation strategies to preserve soil’s physical well-being. Zero-tillage techniques combined with residue retention or incorporation have gained widespread recognition for their capacity to conserve soil and water resources, reduce energy consumption, and enhance soil quality and environmental sustainability. Nevertheless, the choice of tillage and residue management options may vary depending on the geographical locations and specific soil conditions. To assess the impacts of four distinct tillage and residue management approaches, a two-year experiment (2020–2021 and 2021–2022) was conducted: T1: conventional tillage followed by wheat sowing after the removal of rice straw (CT-RS); T2: zero tillage with wheat sowing using a Happy Seeder while retaining rice straw (ZT+RS); T3: conventional tillage followed by wheat sowing after rice straw incorporation using a reversible mouldboard plough (CT+RS); T4: minimum tillage with wheat sowing using a Super Seeder with rice straw incorporation (MT+RS); the effects were recorded on the physical soil properties. Our findings indicate that zero tillage combined with residue retention (T2) had a positive influence on various physical soil attributes. Notably, significant differences were observed among the tillage and residue management options, particularly in terms of the bulk density with T1 exhibiting the highest values and the lowest being in T2, whereas the soil penetration resistance was lowest in T3 compared to T1. In the case of T3, sandy loam and clay loam soils had the highest measured saturated hydraulic conductivity values, measuring 5.08 and 4.57 cm h−1 and 4.07 and 3.73 cm h−1, respectively. Furthermore, T2 (zero tillage with residue retention) demonstrated the highest mean weight diameter (MWD) and maximum water stable aggregate. These results collectively underscore the positive effects of adopting zero tillage and retaining residue (T2) on soil structure and quality, particularly concerning the mechanical and hydrological soil properties.
S-Nitrosylated Proteins Involved in Autophagy in Triticum aestivum Roots: A Bottom-Up Proteomics Approach and In Silico Predictive Algorithms
Authors: Mazina Anastasia , Shumilina Julia , Gazizova Natalia , Repkin Egor , Frolov Andrej , Minibayeva Farida
Published: October 2023

Autophagy is a highly conserved catabolic process in eukaryotic cells. Reactive nitrogen species play roles as inductors and signaling molecules of autophagy. A key mechanism of NO-mediated signaling is S-nitrosylation, a post-translational modification (PTM) of proteins at cysteine residues. In the present work, we analyzed the patterns of protein S-nitrosylation during the induction of autophagy in Triticum aestivum roots. The accumulation of S-nitrosylated proteins in the cells during autophagy induced with KNO2 and antimycin A was visualized using monoclonal antibodies with a Western blot analysis, and proteins were identified using a standard bottom-up proteomics approach. Protein S-nitrosylation is a labile and reversible PTM, and therefore the SNO group can be lost during experimental procedures. A subsequent bioinformatic analysis using predictive algorithms and protein-ligand docking showed that identified proteins possess hypothetical S-nitrosylation sites. Analyzing protein–protein interaction networks enabled us to discover the targets that can directly interact with autophagic proteins, and those that can interact with them indirectly via key multifunctional regulatory proteins. In this study, we show that S-nitrosylation is a key mechanism of NO-mediated regulation of autophagy in wheat roots. A combination of in silico predictive algorithms with a mass spectrometry analysis provides a targeted approach for the identification of S-nitrosylated proteins.
Artificial Intelligence to Early Predict Liver Metastases in Patients with Colorectal Cancer: Current Status and Future Prospectives
Authors: Avella Pasquale , Cappuccio Micaela , Cappuccio Teresa , Rotondo Marco , Fumarulo Daniela , Guerra Germano , Sciaudone Guido , Santone Antonella , Cammilleri Francesco , Bianco Paolo , Brunese Maria Chiara
Published: October 2023

Background: Artificial Intelligence (AI)-based analysis represents an evolving medical field. In the last few decades, several studies have reported the diagnostic efficiency of AI applied to Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) to early detect liver metastases (LM), mainly from colorectal cancer. Despite the increase in information and the development of different procedures in several radiological fields, an accurate method of predicting LM has not yet been found. This review aims to compare the diagnostic efficiency of different AI methods in the literature according to accuracy, sensibility, precision, and recall to identify early LM. Methods: A narrative review of the literature was conducted on PubMed. A total of 336 studies were screened. Results: We selected 17 studies from 2012 to 2022. In total, 14,475 patients were included, and more than 95% were affected by colorectal cancer. The most frequently used imaging tool to early detect LM was found to be CT (58%), while MRI was used in three cases. Four different AI analyses were used: deep learning, radiomics, machine learning, and fuzzy systems in seven (41.18%), five (29.41%), four (23.53%), and one (5.88%) cases, respectively. Four studies achieved an accuracy of more than 90% after MRI and CT scan acquisition, while just two reported a recall rate ≥90% (one method using MRI and CT and one CT). Conclusions: Routinely acquired radiological images could be used for AI-based analysis to early detect LM. Simultaneous use of radiomics and machine learning analysis applied to MRI or CT images should be an effective method considering the better results achieved in the clinical scenario.
In Situ Visible Spectroscopic Daily Monitoring of Senescence of Japanese Maple (Acer palmatum) Leaves
Authors: Nakashima Satoru , Yamakita Eri
Published: October 2023

The degradation of green leaves in autumn after their photosynthetic activities is associated with decreases in chlorophylls and increases in anthocyanins. However, the sequential orders of these processes are not well understood because of a lack of continuous monitoring of leaves in the same positions. Therefore, the senescence processes of Japanese maple (Acer palmatum) leaves were followed daily in the same positions for approximately 60 days using visible spectroscopy with an original handheld visible–near-infrared spectrometer. The obtained reflection spectra were converted to absorption spectra and band areas of chlorophyll a and anthocyanins were determined. Decreases in the chlorophyll a band area with time show two-step exponential decreases corresponding to slow and fast first-order decrease rates. A rapid decrease in chlorophyll a started after an increase in anthocyanin. Therefore, the leaf senescence started through a slow decrease in chlorophyll a (20–30 days), followed by a rapid increase in anthocyanins (~20 days), followed by a rapid decrease in chlorophyll a (10–20 days). The formation of anthocyanins has been proposed to protect leaf cells from losing chlorophylls through solar radiation damage. The obtained sequential changes of pigments support this light screen hypothesis. (199 words < 200 words)
Prostate Cancer Microvascular Routes: Exploration and Measurement Strategies
Authors: Grizzi Fabio , Hegazi Mohamed A. A. A. , Zanoni Matteo , Vota Paolo , Toia Giovanni , Clementi Maria Chiara , Mazzieri Cinzia , Chiriva-Internati Maurizio , Taverna Gianluigi
Published: October 2023

Angiogenesis is acknowledged as a pivotal feature in the pathology of human cancer. Despite the absence of universally accepted markers for gauging the comprehensive angiogenic activity in prostate cancer (PCa) that could steer the formulation of focused anti-angiogenic treatments, the scrutiny of diverse facets of tumoral blood vessel development may furnish significant understanding of angiogenic processes. Malignant neoplasms, encompassing PCa, deploy a myriad of strategies to secure an adequate blood supply. These modalities range from sprouting angiogenesis and vasculogenesis to intussusceptive angiogenesis, vascular co-option, the formation of mosaic vessels, vasculogenic mimicry, the conversion of cancer stem-like cells into tumor endothelial cells, and vascular pruning. Here we provide a thorough review of these angiogenic mechanisms as they relate to PCa, discuss their prospective relevance for predictive and prognostic evaluations, and outline the prevailing obstacles in quantitatively evaluating neovascularization via histopathological examinations.
Change in Time of the Value of Dry and Lubricated Friction Coefficients for Surfaces Generated by Different Processing Methods
Authors: Nagîț Gheorghe , Mihalache Andrei Marius , Dodun Oana , Hrițuc Adelina , Slătineanu Laurențiu , Merticaru Vasile
Published: October 2023

The surfaces of the mechanical parts involved in friction processes are made using different processing methods. Each of these processing methods leads to a certain profile of the asperities of the generated surfaces. When such surfaces are subjected to friction processes, it is possible to produce a change in time in the magnitude of the friction coefficient. For experimental research, the outer cylindrical surfaces of some steel test samples were generated using various machining methods such as turning, grinding, ball and diamond burnishing, and vibroburnishing. Later, using a device adapted to a lathe, experimental tests were carried out following the time variation of the value of the friction coefficient under conditions of dry friction and lubricated friction, respectively. The results of the experimental tests were processed mathematically, being determined by empirical mathematical models that highlight the influence of the final processing methods of the surface, the presence of the lubricant, and the test duration on the variation of the friction coefficient. It was found that first, there is an increase over time in the values of the friction coefficient, and then the values of this coefficient stabilize at certain values. The increase in the coefficient of friction until reaching the stabilization value takes place in a proportion of approximately 148–305%.
Comparison of Microstructure and Mechanical Properties of Ultra-Narrow Gap Metal Active Gas Arc Welded and Narrow Gap Submerged Arc Welded Q235A Low Carbon Steel
Authors: Wu Shang , Xiao Wenkai , Gong Lingfei , Zhang Fuju
Published: October 2023

The 18 mm thick Q235A low carbon steel plates were welded via the ultra-narrow gap metal active gas arc welding (ultra-NGMAGW) and narrow gap submerged arc welding (NGSAW), and the microstructure and mechanical properties of the welded joints’ area were characterized. The results showed that there is acicular ferrite (AF) in the weld zone of the joint obtained via the ultra-NGMAGW. The AF grains are fine and have a great difference in growth direction, resulting in high local dislocation density. However, there is no AF in the welded joint obtained via the NGSAW. Using numerical simulation analysis of the temperature field distribution and the thermal cycle curve in the welding process of the ultra-NGMAGW, it was found that the mechanism of microstructure evolution is that during the welding process of the ultra-NGMAGW, the heat input is low, the cooling rate is quick, and the residence time in the high temperature region is short. Therefore, pearlite with coarse grains is basically not formed. AF nucleates in different directions with inclusions as the core. The tensile strength of the weld joint obtained via the ultra-NGMAGW is 643 MPa, which corresponds to 139% of that of the base metal, and 132% of that obtained via the NGSAW. The ultra-NGMAGW joints exhibited better tensile strength and higher microhardness than the NGSAW joints, which is mainly due to the existence of AF.
Explaining Deep Q-Learning Experience Replay with SHapley Additive exPlanations
Authors: Sullivan Robert S. , Longo Luca
Published: October 2023

Reinforcement Learning (RL) has shown promise in optimizing complex control and decision-making processes but Deep Reinforcement Learning (DRL) lacks interpretability, limiting its adoption in regulated sectors like manufacturing, finance, and healthcare. Difficulties arise from DRL’s opaque decision-making, hindering efficiency and resource use, this issue is amplified with every advancement. While many seek to move from Experience Replay to A3C, the latter demands more resources. Despite efforts to improve Experience Replay selection strategies, there is a tendency to keep the capacity high. We investigate training a Deep Convolutional Q-learning agent across 20 Atari games intentionally reducing Experience Replay capacity from 1×106 to 5×102. We find that a reduction from 1×104 to 5×103 doesn’t significantly affect rewards, offering a practical path to resource-efficient DRL. To illuminate agent decisions and align them with game mechanics, we employ a novel method: visualizing Experience Replay via Deep SHAP Explainer. This approach fosters comprehension and transparent, interpretable explanations, though any capacity reduction must be cautious to avoid overfitting. Our study demonstrates the feasibility of reducing Experience Replay and advocates for transparent, interpretable decision explanations using the Deep SHAP Explainer to promote enhancing resource efficiency in Experience Replay.
Dynamic Behavior of a Stochastic Avian Influenza Model with Two Strains of Zoonotic Virus
Authors: Kong Lili , Li Luping , Kang Shugui , Chen Fu
Published: October 2023

In this paper, a stochastic avian influenza model with two different pathogenic human–avian viruses is studied. The model analyzes the spread of the avian influenza virus from poultry populations to human populations in a random environment. The dynamic behavior of the stochastic avian influenza model is analyzed. Firstly, the existence and uniqueness of a global positive solution are obtained. Secondly, under the condition of high pathogenic virus extinction, the persistence in the mean and extinction of the infected avian population with a low pathogenic virus is analyzed. Thirdly, the sufficient conditions for the existence and uniqueness of the ergodic stationary distribution in the stochastic avian influenza model are derived. We find the threshold of the stochastic model to determine whether the disease spreads when the white noise is small. The analysis results show that random white noise is effective for disease control. Finally, the theoretical results are verified by numerical simulation, and the numerical simulation analysis is carried out for the cases that cannot be theoretically deduced.
Methodology for Assessing the Risks of Regional Competitiveness Based on the Kolmogorov–Chapman Equations
Authors: Chernyshova Galina , Veshneva Irina , Firsova Anna , Makarova Elena L. , Makarova Elena A.
Published: October 2023

The relevance of research on competitiveness at the meso level is related to the contemporary views of a region as an essential element of the economic space. The development of forecasting and analytical methods at the regional level of the economy is a key task in the process of strategic decision making. This article proposes a method of quantitative assessment of the risks of regional competitiveness. The novelty of this approach is based on both a fixed-point risk assessment and scenario-based predictive analysis. A hierarchical structure of indicators of competitiveness of regions is offered. A method based on the Kolmogorov–Chapman equations was used for the predictive estimation of risks of regional competitiveness. The integrated risk assessment is performed using the modified fuzzy ELECTRE II method. A web application has been implemented to assess the risks of competitiveness of Russian regions. The functionality of this application provides the use of multi-criteria decision-making methods based on a fuzzy logic approach to estimate risks at a specified time, calculating the probability of risk events and their combinations in the following periods and visualizing the results. Approbation of the technique was carried out for 78 Russian regions for various scenarios. The analysis of the results obtained provides an opportunity to identify the riskiest factors of regional competitiveness and to distinguish regions with different risk levels.
Deep Learning Algorithms for Behavioral Analysis in Diagnosing Neurodevelopmental Disorders
Authors: Alkahtani Hasan , Ahmed Zeyad , Aldhyani Theyazn , Jadhav Mukti , Alqarni Ahmed
Published: October 2023

Autism spectrum disorder (ASD), or autism, can be diagnosed based on a lack of behavioral skills and social communication. The most prominent method of diagnosing ASD in children is observing the child’s behavior, including some of the signs that the child repeats. Hand flapping is a common stimming behavior in children with ASD. This research paper aims to identify children’s abnormal behavior, which might be a sign of autism, using videos recorded in a natural setting during the children’s regular activities. Specifically, this study seeks to classify self-stimulatory activities, such as hand flapping, as well as normal behavior in real-time. Two deep learning video classification methods are used to be trained on the publicly available Self-Stimulatory Behavior Dataset (SSBD). The first method is VGG-16-LSTM; VGG-16 to spatial feature extraction and long short-term memory networks (LSTM) for temporal features. The second method is a long-term recurrent convolutional network (LRCN) that learns spatial and temporal features immediately in end-to-end training. The VGG-16-LSTM achieved 0.93% on the testing set, while the LRCN model achieved an accuracy of 0.96% on the testing set.
Pontryagin Maximum Principle for Incommensurate Fractional-Orders Optimal Control Problems
Authors: Ndaïrou Faïçal , Torres Delfim F. M.
Published: October 2023

We introduce a new optimal control problem where the controlled dynamical system depends on multi-order (incommensurate) fractional differential equations. The cost functional to be maximized is of Bolza type and depends on incommensurate Caputo fractional-orders derivatives. We establish continuity and differentiability of the state solutions with respect to perturbed trajectories. Then, we state and prove a Pontryagin maximum principle for incommensurate Caputo fractional optimal control problems. Finally, we give an example, illustrating the applicability of our Pontryagin maximum principle.
Large-Scale Simulation of Shor’s Quantum Factoring Algorithm
Authors: Willsch Dennis , Willsch Madita , Jin Fengping , De Raedt Hans , Michielsen Kristel
Published: October 2023

Shor’s factoring algorithm is one of the most anticipated applications of quantum computing. However, the limited capabilities of today’s quantum computers only permit a study of Shor’s algorithm for very small numbers. Here, we show how large GPU-based supercomputers can be used to assess the performance of Shor’s algorithm for numbers that are out of reach for current and near-term quantum hardware. First, we study Shor’s original factoring algorithm. While theoretical bounds suggest success probabilities of only 3–4%, we find average success probabilities above 50%, due to a high frequency of “lucky” cases, defined as successful factorizations despite unmet sufficient conditions. Second, we investigate a powerful post-processing procedure, by which the success probability can be brought arbitrarily close to one, with only a single run of Shor’s quantum algorithm. Finally, we study the effectiveness of this post-processing procedure in the presence of typical errors in quantum processing hardware. We find that the quantum factoring algorithm exhibits a particular form of universality and resilience against the different types of errors. The largest semiprime that we have factored by executing Shor’s algorithm on a GPU-based supercomputer, without exploiting prior knowledge of the solution, is 549,755,813,701 = 712,321 × 771,781. We put forward the challenge of factoring, without oversimplification, a non-trivial semiprime larger than this number on any quantum computing device.
Potential Therapeutic Strategies in the Treatment of Metabolic-Associated Fatty Liver Disease
Authors: Bołdys Aleksandra , Bułdak Łukasz , Maligłówka Mateusz , Surma Stanisław , Okopień Bogusław
Published: October 2023

Metabolic-associated Fatty Liver Disease is one of the outstanding challenges in gastroenterology. The increasing incidence of the disease is undoubtedly connected with the ongoing obesity pandemic. The lack of specific symptoms in the early phases and the grave complications of the disease require an active approach to prompt diagnosis and treatment. Therapeutic lifestyle changes should be introduced in a great majority of patients; but, in many cases, the adherence is not satisfactory. There is a great need for an effective pharmacological therapy for Metabolic-Associated Fatty Liver Disease, especially before the onset of steatohepatitis. Currently, there are no specific recommendations on the selection of drugs to treat liver steatosis and prevent patients from progression toward more advanced stages (steatohepatitis, cirrhosis, and cancer). Therefore, in this Review, we provide data on the clinical efficacy of therapeutic interventions that might improve the course of Metabolic-Associated Fatty Liver Disease. These include the drugs used in the treatment of obesity and hyperlipidemias, as well as affecting the gut microbiota and endocrine system, and other experimental approaches, including functional foods. Finally, we provide advice on the selection of drugs for patients with concomitant Metabolic-Associated Fatty Liver Disease.
IL-1 Beta—A Biomarker for Ischemic Stroke Prognosis and Atherosclerotic Lesions of the Internal Carotid Artery
Authors: Catană Maria-Gabriela , Popențiu Ioan-Adrian , Văleanu Mădălina , Roman-Filip Corina , Mihăilă Romeo-Gabriel
Published: October 2023

Background and Objectives: Stroke is a leading cause of mortality and morbidity worldwide. Treatment of this pathology is still under development and its risk factors remain to be determined. Therefore, we aim to determine the role of interleukin-1 beta in atherosclerotic lesions of the internal carotid artery as a risk factor for stroke and the role of this biomarker in stroke prognosis. Materials and Methods: This study enrolled 56 patients diagnosed with ischemic stroke in the anterior vascular territory (AVT) and posterior vascular territory (PVT). All the patients had venous blood collected at admission and 7 days after the onset of the cerebral ischemia in order to determine the plasma concentration of interleukin-1 beta. At the same time, an extracranial carotid ultrasound was performed. Results: The interleukin-1 beta collected at admission was positively correlated with the NIHSS at admission (Pearson index 0.424), and both measurements were correlated with carotid stenosis (Spearmen correlation index of 0.529 and 0.653, respectively). Conclusions: Interleukin-1 beta could be a reliable biomarker for stroke prognosis and the development of atherosclerotic lesions of the internal carotid.
Serum Osteoprotegerin Levels and the Vascular Reactivity Index in Patients with Hypertension
Authors: Chen Yen-Liang , Huang Po-Yu , Tsai Jen-Pi , Wang Ji-Hung , Hsu Bang-Gee
Published: October 2023

Background and Objectives: Osteoprotegerin (OPG), a soluble glycoprotein found in serum, has been associated with both the presence and severity of atherosclerosis. OPG is regarded as the mediator in the process of vascular endothelial dysfunction. Impaired endothelial function has an intimate link with hypertension (HTN) and is associated with significant morbidity and mortality. This study was to investigate the connection between OPG and endothelial dysfunction in patients having HTN. Materials and Methods: There are 102 patients with HTN included. For the purpose of determining the levels of OPG, a commercial enzyme-linked immunosorbent test kit was applied. The vascular reactivity index (VRI), which is assessed via the digital thermal monitoring, provides information on endothelial function. Results: Ten patients with HTN (9.8%) were classified as having poor vascular reactivity (VRI < 1.0), 46 HTN patients (45.1%) as having intermediate vascular reactivity (1.0 ≤ VRI < 2.0), and 46 HTN patients (45.1%) were classified as having high vascular reactivity (VRI ≥ 2.0). A greater serum OPG level (p < 0.001) and older age (p = 0.022) were linked to impaired vascular reactivity. The estimated glomerular filtration rate (r = 0.196, p = 0.048) was positively correlated with VRI values in hypertensive participants, while advanced age (r = −0.222, p = 0.025) and the log-transformed OPG level (log-OPG, r = −0.357, p < 0.001) were negatively correlated with VRI. Serum log-OPG level was shown to be strongly and independently correlated with VRI values in HTN individuals after multivariable forward stepwise linear regression analysis (β = −0.357, adjusted R2 change = 0.119, p < 0.001). Conclusions: In patients with HTN, serum OPG levels were adversely correlated with VRI and probably had a role in endothelial dysfunction.
Simulation, Fabrication and Microfiltration Using Dual Anodic Aluminum Oxide Membrane
Authors: Qasim Faheem , Ashraf Muhammad Waseem , Tayyaba Shahzadi , Tariq Muhammad Imran , Herrera-May Agustín L.
Published: October 2023

Microfluidic devices have gained subsequent attention due to their controlled manipulation of fluid for various biomedical applications. These devices can be used to study the behavior of fluid under several micrometer ranges within the channel. The major applications are the filtration of fluid, blood filtration and bio-medical analysis. For the filtration of water, as well as other liquids, the micro-filtration based microfluidic devices are considered as potential candidates to fulfill the desired conditions and requirements. The micro pore membrane can be designed and fabricated in such a way that it maximizes the removal of impurities from fluid. The low-cost micro-filtration method has been reported to provide clean fluid for biomedical applications and other purposes. In the work, anodic-aluminum-oxide-based membranes have been fabricated with different pore sizes ranging from 70 to 500 nm. A soft computing technique like fuzzy logic has been used to estimate the filtration parameters. Then, the finite-element-based analysis system software has been used to study the fluid flow through the double membrane. Then, filtration is performed by using a dual membrane and the clogging of the membrane has been studied after different filtration cycles using characterization like a scanning electron microscope. The filtration has been done to purify the contaminated fluid which has impurities like bacteria and protozoans. The membranes have been tested after each cycle to verify the results. The decrease in permeance with respect to the increase in the velocity of the fluid and the permeate volume per unit clearly depicts the removal of containments from the fluid after four and eight cycles of filtration. The results clearly show that the filtration efficiency can be improved by increasing the number of cycles and adding a dual membrane in the micro-fluidic device. The results show the potential of dual anodic aluminum oxide membranes for the effective filtration of fluids for biomedical applications, thereby offering a promising solution to address current challenges.