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19 pages, 6393 KiB  
Article
The Effect of Story Drifts in Determining the Earthquake Performance of High-Rise Buildings
by Mehmet Gokhan Guler and Kadir Guler
Buildings 2024, 14(12), 3830; https://doi.org/10.3390/buildings14123830 (registering DOI) - 29 Nov 2024
Abstract
In performance-based design and assessment, there are prescriptive limits based not only on element-based performance evaluation but also on comparing story drifts with limit values. The process of determining performance levels at the element level involves obtaining the required data through numerous calculation [...] Read more.
In performance-based design and assessment, there are prescriptive limits based not only on element-based performance evaluation but also on comparing story drifts with limit values. The process of determining performance levels at the element level involves obtaining the required data through numerous calculation steps, followed by evaluation, which makes it a time-consuming process. The iterative nature of this process emphasizes the importance of selecting the structural system, element dimensions, and target performance levels during the preliminary design stage to ensure they are consistent with the final analysis results. For this purpose, the determination of story drifts, which is widely accepted in the literature, is a critical aspect of performance evaluation studies, particularly for high-rise buildings, within the framework of deformation-based calculation assumptions. The continuum model is a practical approach for the approximate analysis of high-rise buildings including moment-resisting frames and shear wall-frame systems. In the continuum model, discrete buildings are simplified such that their overall behavior is described through the contributions of flexural and shear stiffnesses at the story levels. In this study, the aim is to enhance the Miranda and Taghavi (2005) model, which is classified among the approximate methods in the literature for determining story drifts and is developed within the framework of continuum model approaches. Full article
(This article belongs to the Section Building Structures)
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12 pages, 22206 KiB  
Article
Accurate Discrimination of Mold-Damaged Citri Reticulatae Pericarpium Using Partial Least-Squares Discriminant Analysis and Selected Wavelengths
by Huizhen Tan, Yang Liu, Hui Tang, Wei Fan, Liwen Jiang and Pao Li
Foods 2024, 13(23), 3856; https://doi.org/10.3390/foods13233856 (registering DOI) - 29 Nov 2024
Abstract
Unscrupulous merchants sell the mold-damaged Citri Reticulatae Pericarpium (CRP) after removing the mold. In this study, an accurate and non-destructive strategy was developed for the discrimination of mold-damaged CRPs using portable near-infrared (NIR) spectroscopy and chemometrics. The outer surface and inner surface spectra [...] Read more.
Unscrupulous merchants sell the mold-damaged Citri Reticulatae Pericarpium (CRP) after removing the mold. In this study, an accurate and non-destructive strategy was developed for the discrimination of mold-damaged CRPs using portable near-infrared (NIR) spectroscopy and chemometrics. The outer surface and inner surface spectra were obtained without destroying CRPs. The discrimination models were established using partial least squares-discriminant analysis (PLS-DA) and wavelength selection strategy was used to further improve the discrimination ability. The predictive ability of models was assessed using the test set and an independent test set obtained one month later. The results demonstrate that the models of the outer surface outperform those of the inner surface. With multiplicative scatter correction (MSC)-PLS-DA, 100% accuracies were obtained in test and independent test sets. Furthermore, the wavelength selection strategy simplified the models with 100% discrimination accuracy. In addition, the randomization test (RT)-PLS-DA model developed in this study combines both the benefits of high accuracy and robustness, which can be applied for the accurate discrimination of mold-damaged CRPs. Full article
(This article belongs to the Special Issue Detecting the Quality and Geographic Origin of Agri-Food Products by Using Spectroscopic Methods)
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21 pages, 2725 KiB  
Article
Impact of Gold Nanoparticles and Ionizing Radiation on Whole Chromatin Organization as Detected by Single-Molecule Localization Microscopy
by Myriam Schäfer, Georg Hildenbrand and Michael Hausmann
Int. J. Mol. Sci. 2024, 25(23), 12843; https://doi.org/10.3390/ijms252312843 (registering DOI) - 29 Nov 2024
Abstract
In radiation tumor therapy, irradiation, on one hand, should cause cell death to the tumor. On the other hand, the surrounding non-tumor tissue should be maintained unaffected. Therefore, methods of local dose enhancements are highly interesting. Gold nanoparticles, which are preferentially uptaken by [...] Read more.
In radiation tumor therapy, irradiation, on one hand, should cause cell death to the tumor. On the other hand, the surrounding non-tumor tissue should be maintained unaffected. Therefore, methods of local dose enhancements are highly interesting. Gold nanoparticles, which are preferentially uptaken by very-fast-proliferating tumor cells, may enhance damaging. However, the results in the literature obtained from cell culture and animal tissue experiments are very contradictory, i.e., only some experiments reveal increased cell killing but others do not. Thus, a better understanding of cellular mechanisms is required. Using the breast cancer cell model SkBr3, the effects of gold nanoparticles in combination with ionizing radiation on chromatin network organization were investigated by Single-Molecule Localization Microscopy (SMLM) and applications of mathematical topology calculations (e.g., Persistent Homology, Principal Component Analysis, etc.). The data reveal a dose and nanoparticle dependent re-organization of chromatin, although colony forming assays do not show a significant reduction of cell survival after the application of gold nanoparticles to the cells. In addition, the spatial organization of γH2AX clusters was elucidated, and characteristic changes were obtained depending on dose and gold nanoparticle application. The results indicate a complex response of ALU-related chromatin and heterochromatin organization correlating to ionizing radiation and gold nanoparticle incorporation. Such complex whole chromatin re-organization is usually associated with changes in genome function and supports the hypothesis that, with the application of gold nanoparticles, not only is DNA damage increasing but also the efficiency of DNA repair may be increased. The understanding of complex chromatin responses might help to improve the gold nanoparticle efficiency in radiation treatment. Full article
(This article belongs to the Special Issue Metal Nanoparticles: From Fundamental Studies to New Applications)
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22 pages, 2168 KiB  
Review
The Role of Protein Kinase C During the Differentiation of Stem and Precursor Cells into Tissue Cells
by Oliver Pieles and Christian Morsczeck
Biomedicines 2024, 12(12), 2735; https://doi.org/10.3390/biomedicines12122735 (registering DOI) - 29 Nov 2024
Abstract
Protein kinase C (PKC) plays an essential role during many biological processes including development from early embryonic stages until the terminal differentiation of specialized cells. This review summarizes the current knowledge about the involvement of PKC in molecular processes during the differentiation of [...] Read more.
Protein kinase C (PKC) plays an essential role during many biological processes including development from early embryonic stages until the terminal differentiation of specialized cells. This review summarizes the current knowledge about the involvement of PKC in molecular processes during the differentiation of stem/precursor cells into tissue cells with a particular focus on osteogenic, adipogenic, chondrogenic and neuronal differentiation by using a comprehensive approach. Interestingly, studies examining the overall role of PKC, or one of its three isoform groups (classical, novel and atypical PKCs), often showed controversial results. A discrete observation of distinct isoforms demonstrated that the impact on differentiation differs highly between the isoforms, and that during a certain process, the influence of only some isoforms is crucial, while others are less important. In particular, PKCβ inhibits, and PKCδ strongly supports osteogenesis, whereas it is the other way around for adipogenesis. PKCε is another isoform that overwhelmingly supports adipogenic differentiation. In addition, PKCα plays an important role in chondrogenesis, while neuronal differentiation has been positively associated with numerous isoforms including classical, novel and atypical PKCs. In a cellular context, various upstream mediators, like the canonical and non-canonical Wnt pathways, endogenously control PKC activity and thus, their activity interferes with the influence of PKC on differentiation. Downstream of PKC, several proteins and pathways build the molecular bridge between the enzyme and the control of differentiation, of which only a few have been well characterized so far. In this context, PKC also cooperates with other kinases like Akt or protein kinase A (PKA). Furthermore, PKC is capable of directly phosphorylating transcription factors with pivotal function for a certain developmental process. Ultimately, profound knowledge about the role of distinct PKC isoforms and the involved signaling pathways during differentiation constitutes a promising tool to improve the use of stem cells in regenerative therapies by precisely manipulating the activity of PKC or downstream effectors. Full article
(This article belongs to the Section Cell Biology and Pathology)
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28 pages, 4680 KiB  
Article
Scheduling a Fleet of Dynamic EV Chargers for Maximal Profile
by Shorooq Alaskar and Mohamed Younis
Energies 2024, 17(23), 6009; https://doi.org/10.3390/en17236009 (registering DOI) - 29 Nov 2024
Abstract
The proliferation of electric vehicles (EVs) faces obstacles like range anxiety and inadequate charging infrastructure. To address these challenges, dynamic EV-to-EV charging technology has emerged. This innovative method enables one EV with surplus battery to charge another EV while both are in motion. [...] Read more.
The proliferation of electric vehicles (EVs) faces obstacles like range anxiety and inadequate charging infrastructure. To address these challenges, dynamic EV-to-EV charging technology has emerged. This innovative method enables one EV with surplus battery to charge another EV while both are in motion. This study focuses on efficiently pairing and routing energy suppliers (ESs) to meet energy requesters (ERs) and transfer energy via platooning. The key objective is to manage the ES fleet effectively, framed as a vehicle routing problem, to maximize profit by serving as many energy requests as possible. We formulate the problem as an integer programming model within a time-space network and propose a local search-based heuristic algorithm designed to efficiently handle large-scale networks. Numerical experiments conducted on Sioux Falls validate the efficacy of our approach, allowing for an assessment of algorithm performance under realistic large-scale conditions. The findings illustrate enhancements in ER travel time and energy overhead, alongside maximized profits for ESs. Full article
(This article belongs to the Special Issue Electric and Hydrogen Vehicles in Urban Transport Systems: The Current State, Plans, and Technical Requirements)
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22 pages, 4788 KiB  
Article
Experiments and Heat Transfer Correlation Validations of Low-Parameter Region of sCO2 Flow in a Long Thin Vertical Loop
by Rufan Song, Yongchang Feng, Dong Yang, Gang Zeng, Deqing Mei, Igor Pioro and Lin Chen
Energies 2024, 17(23), 6010; https://doi.org/10.3390/en17236010 (registering DOI) - 29 Nov 2024
Abstract
The focus of this study is to accurately predict the convective heat transfer of CO2 to ensure the safe and efficient design of supercritical and trans-critical CO2 energy systems. The heat transfer performance of CO2 is crucial for the stable [...] Read more.
The focus of this study is to accurately predict the convective heat transfer of CO2 to ensure the safe and efficient design of supercritical and trans-critical CO2 energy systems. The heat transfer performance of CO2 is crucial for the stable operation of these systems. This research study explored the flow and heat transfer behavior of CO2 in a long thin vertical loop through experiments. A range of key parameters were set in the experiments to ensure the broad coverage of operating conditions. The inlet temperature was set between 10 °C and 45 °C, the pressure ranged from 6.0 to 9.0 MPa, mass fluxes varied from 500 to 1500 kg/m2s, and the heat flux reached up to 300 kW/m2. Experiments were performed at Reynolds number 104. By adjusting these parameters, the experiments were able to simulate CO2 heat transfer performance under various real-world conditions. Additionally, numerical simulations were employed to further analyze CO2’s flow and heat transfer behavior. Different turbulence models were tested, and the results showed that the SST k-ω model can best predict CO2 convective heat transfer, effectively capturing the complex heat transfer characteristics under varying flow conditions. The research outcomes were compared with established correlations through the Nusselt number, and while a ±30% uncertainty was observed, the overall agreement was satisfactory. This indicates that the experimental and simulation results are within a reasonable range, confirming their reliability. Full article
(This article belongs to the Section J1: Heat and Mass Transfer)
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13 pages, 5396 KiB  
Article
A Novel Approach to DBS Electrode Prototyping
by Jesús Eduardo Medina-Rodríguez, Armando Josue Piña-Díaz, Juan Alejandro Flores-Campos, Karla Nayeli Silva-Garces, Armando Oropeza-Osornio and Christopher René Torres San Miguel
Processes 2024, 12(12), 2694; https://doi.org/10.3390/pr12122694 (registering DOI) - 29 Nov 2024
Abstract
This research project focuses on the design and fabrication of a deep brain stimulation (DBS) electrode used for Parkinson’s disease. It is a combination of technologies, such as 3D printing injection of polymers and silicones at high and low temperatures, used to develop [...] Read more.
This research project focuses on the design and fabrication of a deep brain stimulation (DBS) electrode used for Parkinson’s disease. It is a combination of technologies, such as 3D printing injection of polymers and silicones at high and low temperatures, used to develop a manufacturing process of a DBS electrode prototype. For the manufacturing process of the DBS electrode, two case studies are proposed, one at high temperature and the other at room temperature. Rings are used for communication at the ends with the deep brain stimulation (DBS). For the development, different types of molds and nozzles were proposed, considering various variables to control the material flow since polymers or copolymers melted at high temperatures behave differently from silicones injected at room temperature. The injection of Polyamide as a coating for a silver core in a mold, as well as the injection of silicone over a steel core, have been applied theoretically and experimentally. The results show a new method and technique to produce DBS electrodes at a low cost. Full article
(This article belongs to the Special Issue Processes in Industry 4.0/5.0: Automation, Robotics and Smart Manufacturing)
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16 pages, 29747 KiB  
Article
Identification of Elephant Rumbles in Seismic Infrasonic Signals Using Spectrogram-Based Machine Learning
by Janitha Vidunath, Chamath Shamal, Ravindu Hiroshan, Udani Gamlath, Chamira U. S. Edussooriya and Sudath R. Munasinghe
Appl. Syst. Innov. 2024, 7(6), 117; https://doi.org/10.3390/asi7060117 (registering DOI) - 29 Nov 2024
Abstract
This paper presents several machine learning methods and highlights the most effective one for detecting elephant rumbles in infrasonic seismic signals. The design and implementation of electronic circuitry to amplify, filter, and digitize the seismic signals captured through geophones are presented. The process [...] Read more.
This paper presents several machine learning methods and highlights the most effective one for detecting elephant rumbles in infrasonic seismic signals. The design and implementation of electronic circuitry to amplify, filter, and digitize the seismic signals captured through geophones are presented. The process converts seismic rumbles to a spectrogram and the existing methods of spectrogram feature extraction and appropriate machine learning algorithms are compared on their merit for automatic seismic rumble identification. A novel method of denoising the spectrum that leads to enhanced accuracy in identifying seismic rumbles is presented. It is experimentally found that the combination of the Mel-frequency cepstral coefficient (MFCC) feature extraction method and the ridge classifier machine learning algorithm give the highest accuracy of 97% in detecting infrasonic elephant rumbles hidden in seismic signals. The trained machine learning algorithm can run quite efficiently on general-purpose embedded hardware such as a Raspberry Pi, hence the method provides a cost-effective and scalable platform to develop a tool to remotely localize elephants, which would help mitigate the human–elephant conflict. Full article
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23 pages, 2436 KiB  
Article
Expert-Trajectory-Based Features for Apprenticeship Learning via Inverse Reinforcement Learning for Robotic Manipulation
by Francisco J. Naranjo-Campos, Juan G. Victores and Carlos Balaguer
Appl. Sci. 2024, 14(23), 11131; https://doi.org/10.3390/app142311131 (registering DOI) - 29 Nov 2024
Abstract
This paper explores the application of Inverse Reinforcement Learning (IRL) in robotics, focusing on inferring reward functions from expert demonstrations of robot arm manipulation tasks. By leveraging IRL, we aim to develop efficient and adaptable techniques for learning robust solutions to complex tasks [...] Read more.
This paper explores the application of Inverse Reinforcement Learning (IRL) in robotics, focusing on inferring reward functions from expert demonstrations of robot arm manipulation tasks. By leveraging IRL, we aim to develop efficient and adaptable techniques for learning robust solutions to complex tasks in continuous state spaces. Our approach combines Apprenticeship Learning via IRL with Proximal Policy Optimization (PPO), expert-trajectory-based features, and the application of a reverse discount. The feature space is constructed by sampling expert trajectories to capture essential task characteristics, enhancing learning efficiency and generalizability by concentrating on critical states. To prevent the vanishing of feature expectations in goal states, we introduce a reverse discounting application to prioritize feature expectations in final states. We validate our methodology through experiments in a simple GridWorld environment, demonstrating that reverse discounting enhances the alignment of the agent’s features with those of the expert. Additionally, we explore how the parameters of the proposed feature definition influence performance. Further experiments on robotic manipulation tasks using the TIAGo robot compare our approach with state-of-the-art methods, confirming its effectiveness and adaptability in complex continuous state spaces across diverse manipulation tasks. Full article
(This article belongs to the Special Issue Automation and Intelligent Control for Robotics)
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19 pages, 4858 KiB  
Article
Assessment of the Mechanical Properties and Fragment Characteristics of a 3D-Printed Forearm Orthosis
by Mislav Majdak, Slavica Bogović, Maja Somogyi Škoc and Iva Rezić Meštrović
Polymers 2024, 16(23), 3349; https://doi.org/10.3390/polym16233349 (registering DOI) - 29 Nov 2024
Abstract
Distal radius fractures (DRF) are one of the most prevalent injuries a person may sustain. The current treatment of DRF involves the use of casts made from Plaster of Paris or fiberglass. The application of these materials is a serious endeavor that influences [...] Read more.
Distal radius fractures (DRF) are one of the most prevalent injuries a person may sustain. The current treatment of DRF involves the use of casts made from Plaster of Paris or fiberglass. The application of these materials is a serious endeavor that influences their intended use, and should be conducted by specially trained personnel. In this research, with the use of the full-body 3D scanner Vitus Smart, 3D modelling software Rhinoceros 3D, and 3D printer Creality CR-10 max, an easy, yet effective workflow of orthosis fabrication was developed. Furthermore, samples that represent segments of the orthosis were subjected to static loading. Lastly, fragments that occurred due to excessive force were characterized with the use of a digital microscope. It was observed that with the implementation of the designed workflow, a faster 3D printing process was present. Samples subjected to mechanical loading had values that exceeded those of conventional Plaster of Paris; the minimum recorded value was 681 N, while the highest was 914 N. Microscopic characterization enabled a clear insight into the occurrence of fragments, as well as their potential risk. Therefore, in this research, an insight into different stages of fabrication, characterization of undesirable events, as well as the risks they may pose were presented. Full article
(This article belongs to the Special Issue Advanced Additive Processes and 3D Printing for Polymer Composites, 2nd Edition)
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17 pages, 618 KiB  
Article
Enhancing Pereskia aculeata Mill. Cultivation with LED Technology: A Sustainable Approach
by Nayara Vieira Silva, Ailton Cesar Lemes, Fabiano Guimarães Silva, Bruno Matheus Mendes Dário, Jenifer Ribeiro de Jesus, Tainara Leal de Sousa, Sibele Santos Fernandes and Mariana Buranelo Egea
Processes 2024, 12(12), 2695; https://doi.org/10.3390/pr12122695 (registering DOI) - 29 Nov 2024
Abstract
Using light-emitting diode (LED) in plant production optimizes growth with higher energy efficiency, reduces carbon footprint and resource consumption, and promotes more sustainable agriculture. However, the plants’ growth characteristics and biochemical composition may vary depending on the light’s wavelength, spectrum, and intensity. Therefore, [...] Read more.
Using light-emitting diode (LED) in plant production optimizes growth with higher energy efficiency, reduces carbon footprint and resource consumption, and promotes more sustainable agriculture. However, the plants’ growth characteristics and biochemical composition may vary depending on the light’s wavelength, spectrum, and intensity. Therefore, LEDs as a light source have become a promising choice for improving cultivation efficiency, as they can modulate the spectrum to meet the needs of plants. Pereskia aculeata is a plant species from the cactus family with high protein, vitamins, minerals, and fiber. The objective of this study was to evaluate the effect of LED lighting on the cultivation of P. aculeata and its influence on biometric color and physicochemical aspects. Two treatments were carried out without the addition of artificial light: one inside the greenhouse (C-ins) and the other outside the greenhouse (C-out), and four treatments with LEDs in different spectral bands: monochromatic red (600–700 nm) (Red), monochromatic blue (400–490 nm) (Blue), white (400–700 nm) (White), and blue–red (1:1) (Blue–Red). The biometric characteristics and the color of the leaves collected from the different treatments were evaluated. After this, the leaves were dried, ground, and evaluated. The physicochemical and thermal characteristics, bioactive compounds, and antioxidant activity of the leaves from each treatment were described. The biometric characteristics were intensified with red LED, and the color of the leaves tended toward green. The dried yield was around 50%, except for C-out treatment. Regarding nutritional characteristics, the highest protein (29.68 g/100 g), fiber (34.44 g/100 g), ash (20.28 g/100 g), and lipid (3.44 g/100 g) contents were obtained in the treatment with red light. The red treatment also intensified the content of chlorophyll a (28.27 µg/L) and total carotenoids (5.88 µg/g). The blue treatment intensified the concentration of minerals and provided greater thermal stability. Regarding bioactive properties, the cultivation of P. aculeata inside the greenhouse favored the concentration of phenolic compounds and a greater antioxidant capacity. Therefore, the quality of light for P. aculeata demonstrates that the length of red and blue light corroborates the development of the plant through the wavelength absorbed by the leaves, favoring its characteristics and planting in closed environments. Full article
(This article belongs to the Special Issue Circular Economy and Efficient Use of Resources (Volume II))
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15 pages, 2651 KiB  
Article
TrAnnoScope: A Modular Snakemake Pipeline for Full-Length Transcriptome Analysis and Functional Annotation
by Aysevil Pektas, Frank Panitz and Bo Thomsen
Genes 2024, 15(12), 1547; https://doi.org/10.3390/genes15121547 (registering DOI) - 29 Nov 2024
Abstract
Background/Objectives: Transcriptome assembly and functional annotation are essential in understanding gene expression and biological function. Nevertheless, many existing pipelines lack the flexibility to integrate both short- and long-read sequencing data or fail to provide a complete, customizable workflow for transcriptome analysis, particularly [...] Read more.
Background/Objectives: Transcriptome assembly and functional annotation are essential in understanding gene expression and biological function. Nevertheless, many existing pipelines lack the flexibility to integrate both short- and long-read sequencing data or fail to provide a complete, customizable workflow for transcriptome analysis, particularly for non-model organisms. Methods: We present TrAnnoScope, a transcriptome analysis pipeline designed to process Illumina short-read and PacBio long-read data. The pipeline provides a complete, customizable workflow to generate high-quality, full-length (FL) transcripts with broad functional annotation. Its modular design allows users to adapt specific analysis steps for other sequencing platforms or data types. The pipeline encompasses steps from quality control to functional annotation, employing tools and established databases such as SwissProt, Pfam, Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and Eukaryotic Orthologous Groups (KOG). As a case study, TrAnnoScope was applied to RNA-Seq and Iso-Seq data from zebra finch brain, ovary, and testis tissue. Results: The zebra finch transcriptome generated by TrAnnoScope from the brain, ovary, and testis tissue demonstrated strong alignment with the reference genome (99.63%), and it was found that 93.95% of the matched protein sequences in the zebra finch proteome were captured as nearly complete. Functional annotation provided matches to known protein databases and assigned relevant functional terms to the majority of the transcripts. Conclusions: TrAnnoScope successfully integrates short and long sequencing technologies to generate transcriptomes with minimal user input. Its modularity and ease of use make it a valuable tool for researchers analyzing complex datasets, particularly for non-model organisms. Full article
(This article belongs to the Section Bioinformatics)
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17 pages, 6427 KiB  
Article
The PEPCK and FBP Genes Regulate Gluconeogenesis Metabolism in Grape Berries in Response to Light Intensity
by Zhongyi Yang, Leyi Shen, Lingling Hu, Yingjian Cai, Qianqian Zheng and Yueyan Wu
Horticulturae 2024, 10(12), 1270; https://doi.org/10.3390/horticulturae10121270 (registering DOI) - 29 Nov 2024
Abstract
Sugar–acid metabolism is a key factor in determining grape quality, and gluconeogenesis is one of the important sugar–acid metabolic pathways. To explore the effects of reduced light intensity on grape berry quality and gluconeogenesis under greenhouse cultivation, we used the ‘Shine Muscat’ cultivar. [...] Read more.
Sugar–acid metabolism is a key factor in determining grape quality, and gluconeogenesis is one of the important sugar–acid metabolic pathways. To explore the effects of reduced light intensity on grape berry quality and gluconeogenesis under greenhouse cultivation, we used the ‘Shine Muscat’ cultivar. With decreasing light intensity, the photosynthetic activity in the grape leaves decreased, resulting in significant reductions in the net photosynthetic rate, transpiration intensity, and stomatal conductance while reducing organic matter accumulation, thus significantly affecting subsequent grape berry quality and gluconeogenesis. Shade treatment inhibited the accumulation of glucose, fructose, and soluble solids in the grape berries but promoted the accumulation of malic acid, tartaric acid, and citric acid. PEPCK and FBP are the key genes underlying the effect of light intensity on gluconeogenesis in grape berries, with PEPCK being involved mainly in tartaric acid metabolism and FBP being involved in malic acid, citric acid, and tartaric acid metabolism. Full article
(This article belongs to the Section Viticulture)
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8 pages, 3226 KiB  
Case Report
A Rare Case of a Large Composite Endometrioma–Mature Cystic Teratoma: The Importance of Surgical Treatment and Pathologic Diagnosis
by Jun Song and Caitlin Martin
Reprod. Med. 2024, 5(4), 280-287; https://doi.org/10.3390/reprodmed5040024 (registering DOI) - 29 Nov 2024
Abstract
Endometriosis is a common benign gynecologic disorder associated with infertility and pelvic pain, affecting 6–11% of reproductive-age females, and can frequently lead to the formation of ovarian endometriomas. Mature cystic teratomas are benign ovarian tumors comprising 10–25% of ovarian tumors. Both pathologies are [...] Read more.
Endometriosis is a common benign gynecologic disorder associated with infertility and pelvic pain, affecting 6–11% of reproductive-age females, and can frequently lead to the formation of ovarian endometriomas. Mature cystic teratomas are benign ovarian tumors comprising 10–25% of ovarian tumors. Both pathologies are common individually but rarely coexist. The case presented here describes a 49-year-old female presenting with a large composite endometrioma–mature cystic teratoma, a rare occurrence with few documented cases. The patient had a 24 cm × 17 cm × 15 cm adnexal mass identified via imaging, which was surgically removed. Pathology confirmed a composite tumor, with the teratoma encased within the endometrioma. This case underscores the importance of surgical management in complex adnexal masses to obtain tissue for definitive diagnosis and to exclude malignancy. Given the rarity of such coexistence and the challenges in preoperative diagnosis, surgical intervention is crucial for accurate diagnosis and effective management. Full article
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18 pages, 44302 KiB  
Article
DuSiamIE: A Lightweight Multidimensional Infrared-Enhanced RGBT Tracking Algorithm for Edge Device Deployment
by Jiao Li, Haochen Wu, Yuzhou Gu, Junyu Lu and Xuecheng Sun
Electronics 2024, 13(23), 4721; https://doi.org/10.3390/electronics13234721 (registering DOI) - 29 Nov 2024
Abstract
Advancements in deep learning and infrared sensors have facilitated the integration of RGB-thermal (RGBT) tracking technology in computer vision. However, contemporary RGBT tracking methods handle complex image data, resulting in inference procedures with a large number of floating-point operations and parameters, which limits [...] Read more.
Advancements in deep learning and infrared sensors have facilitated the integration of RGB-thermal (RGBT) tracking technology in computer vision. However, contemporary RGBT tracking methods handle complex image data, resulting in inference procedures with a large number of floating-point operations and parameters, which limits their performance on general-purpose processors. We present a lightweight Siamese dual-stream infrared-enhanced RGBT tracking algorithm, called DuSiamIE.It is implemented on the low-power NVIDIA Jetson Nano to assess its practicality for edge-device applications in resource-limited settings. Our algorithm replaces the conventional backbone network with a modified MobileNetV3 and incorporates light-aware and infrared feature enhancement modules to extract and integrate multimodal information. Finally, NVIDIA TensorRT is used to improve the inference speed of the algorithm on edge devices. We validated our algorithm on two public RGBT tracking datasets. On the GTOT dataset, DuSiamIE achieved a precision (PR) of 83.4% and a success rate (SR) of 66.8%, with a tracking speed of 40.3 frames per second (FPS). On the RGBT234 dataset, the algorithm achieved a PR of 75.3% and an SR of 52.6%, with a tracking speed of 34.7 FPS. Compared with other algorithms, DuSiamIE exhibits a slight loss in accuracy but significantly outperforms them in speed on resource-constrained edge devices. It is the only algorithm among those tested that can perform real-time tracking on such devices. Full article
(This article belongs to the Special Issue Machine Learning and Deep Learning Based Pattern Recognition)
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14 pages, 311 KiB  
Review
Advances in Induced Pluripotent Stem Cell-Derived Natural Killer Cell Therapy
by Wenhua Qiao, Peng Dong, Hui Chen and Jianmin Zhang
Cells 2024, 13(23), 1976; https://doi.org/10.3390/cells13231976 (registering DOI) - 29 Nov 2024
Abstract
Natural killer (NK) cells are cytotoxic lymphocytes of the innate immune system capable of killing virus-infected cells and/or cancer cells. The commonly used NK cells for therapeutic applications include primary NK cells and immortalized NK cell lines. However, primary NK cell therapy faces [...] Read more.
Natural killer (NK) cells are cytotoxic lymphocytes of the innate immune system capable of killing virus-infected cells and/or cancer cells. The commonly used NK cells for therapeutic applications include primary NK cells and immortalized NK cell lines. However, primary NK cell therapy faces limitations due to its restricted proliferation capacity and challenges in stable storage. Meanwhile, the immortalized NK-92 cell line requires irradiation prior to infusion, which reduces its cytotoxic activity, providing a ready-made alternative and overcoming these bottlenecks. Recent improvements in differentiation protocols for iPSC-derived NK cells have facilitated the clinical production of iPSC-NK cells. Moreover, iPSC-NK cells can be genetically modified to enhance tumor targeting and improve the expansion and persistence of iPSC-NK cells, thereby achieving more robust antitumor efficacy. This paper focuses on the differentiation-protocols efforts of iPSC-derived NK cells and the latest progress in iPSC-NK cell therapy. Additionally, we discuss the current challenges faced by iPSC-NK cells and provide an outlook on future applications and developments. Full article
14 pages, 5281 KiB  
Article
Zirconium–Polycarboxylato Gel Systems as Substrates to Develop Advanced Fluorescence Sensing Devices
by Jon Pascual-Colino, Garikoitz Beobide, Oscar Castillo, Javier Cepeda, Mónica Lanchas, Antonio Luque and Sonia Pérez-Yáñez
Gels 2024, 10(12), 783; https://doi.org/10.3390/gels10120783 (registering DOI) - 29 Nov 2024
Abstract
This study presents the development of zirconium polycarboxylate gel systems as substrates for advanced fluorescence sensing devices. Zirconium-based metal–organic gels (MOGs) offer a promising alternative due to the robustness of the Zr–O bond, which provides enhanced chemical stability. In this work, zirconium polycarboxylate [...] Read more.
This study presents the development of zirconium polycarboxylate gel systems as substrates for advanced fluorescence sensing devices. Zirconium-based metal–organic gels (MOGs) offer a promising alternative due to the robustness of the Zr–O bond, which provides enhanced chemical stability. In this work, zirconium polycarboxylate gels were synthesized using green solvents in a rapid room temperature method. Fluorescein, naphthalene-2,6-dicarboxylic acid, and 4,4′,4″,4‴-(porphine-5,10,15,20-tetrayl)tetrakisbenzoic acid were incorporated as fluorophores to give the gel luminescent properties, enabling it to be used as a sensor. These fluorophores produce specific changes in the perceived color and intensity of the fluorescence emission upon interaction with different analytes in a solution, allowing a qualitative identification of different solvents and compounds. However, the fragile structure of neat gels hinders reproducible quantitative analysis of fluorescence emission. Therefore, to increase their mechanical stability during manipulation, a composite material was developed by combining the MOGs with quartz microcrystals, which proved to be a more reliable fluorescent system. The results show that the material can identify univocally different solvents and analytes in aqueous solutions by the quantitative analysis of the emission intensities. This work presents an innovative approach to create advanced fluorescence sensors with improved mechanical properties and stability using zirconium polycarboxylate gels and multiple fluorophores. Full article
(This article belongs to the Special Issue Outcomes and Trends in Polymer Gels: Designing, Properties and Applications)
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20 pages, 1049 KiB  
Review
The Interactions Between Diet and Gut Microbiota in Preventing Gestational Diabetes Mellitus: A Narrative Review
by Luiza-Andreea Beldie, Cristina-Camelia Dica, Maria Moța, Bianca-Florentina Pirvu, Marilena-Alexandra Burticală, Adina Mitrea, Diana Clenciu, Ion Cristian Efrem, Beatrice Elena Vladu, Diana Cristina Protasiewicz Timofticiuc, Maria Magdalena Roșu, Theodora Claudia Gheonea, Anca Maria Amzolini, Eugen Moța and Ionela Mihaela Vladu
Nutrients 2024, 16(23), 4131; https://doi.org/10.3390/nu16234131 (registering DOI) - 29 Nov 2024
Abstract
Recent studies have revealed that dysbiosis, defined as alterations in gut microbiota, plays an important role in the development and the progression of many non-communicable diseases, including metabolic disorders, such as type 2 diabetes mellitus and gestational diabetes mellitus (GDM). The high frequency [...] Read more.
Recent studies have revealed that dysbiosis, defined as alterations in gut microbiota, plays an important role in the development and the progression of many non-communicable diseases, including metabolic disorders, such as type 2 diabetes mellitus and gestational diabetes mellitus (GDM). The high frequency of GDM makes this disorder an important public health issue, which needs to be addressed in order to reduce both the maternal and fetal complications that are frequently associated with this disease. The studies regarding the connections between gut dysbiosis and GDM are still in their early days, with new research continuously emerging. This narrative review seeks to outline the mechanisms through which a healthy diet that protects the gut microbiota is able to prevent the occurrence of GDM, thus providing medical nutritional therapeutic perspectives for the management of GDM. Full article
(This article belongs to the Special Issue Nutritional Supplements for Gestational Diabetes)
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19 pages, 12268 KiB  
Article
Potential Drug Synergy Through the ERBB2 Pathway in HER2+ Breast Tumors
by Yareli Rojas-Salazar, Emiliano Gómez-Montañez, Jorge Rojas-Salazar, Guillermo de Anda-Jáuregui and Enrique Hernández-Lemus
Int. J. Mol. Sci. 2024, 25(23), 12840; https://doi.org/10.3390/ijms252312840 (registering DOI) - 29 Nov 2024
Abstract
HER2-positive (HER2+) breast cancer is characterized by the overexpression of the ERBB2 (HER2) gene, which promotes aggressive tumor growth and poor prognosis. Targeting the ERBB2 pathway with single-agent therapies has shown limited efficacy due to resistance mechanisms and the complexity of gene interactions [...] Read more.
HER2-positive (HER2+) breast cancer is characterized by the overexpression of the ERBB2 (HER2) gene, which promotes aggressive tumor growth and poor prognosis. Targeting the ERBB2 pathway with single-agent therapies has shown limited efficacy due to resistance mechanisms and the complexity of gene interactions within the tumor microenvironment. This study aims to explore potential drug synergies by analyzing gene–drug interactions and combination therapies that target the ERBB2 pathway in HER2+ breast tumors. Using gene co-expression network analysis, we identified 23 metabolic pathways with significant cross-linking of gene interactions, including those involving EGFR tyrosine kinase inhibitors, PI3K, mTOR, and others. We visualized these interactions using Cytoscape to generate individual and combined drug–gene networks, focusing on frequently used drugs such as Erlotinib, Gefitinib, Lapatinib, and Cetuximab. Individual networks highlighted the direct effects of these drugs on their target genes and neighboring genes within the ERBB2 pathway. Combined drug networks, such as those for Cetuximab with Lapatinib, Cetuximab with Erlotinib, and Erlotinib with Lapatinib, revealed potential synergies that could enhance therapeutic efficacy by simultaneously influencing multiple genes and pathways. Our findings suggest that a network-based approach to analyzing drug combinations provides valuable insights into the molecular mechanisms of HER2+ breast cancer and offers promising strategies for overcoming drug resistance and improving treatment outcomes. Full article
(This article belongs to the Special Issue Molecular Research and Cellular Biology of Breast Cancer)
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34 pages, 4906 KiB  
Review
Progress in Aluminum-Based Composites Prepared by Stir Casting: Mechanical and Tribological Properties for Automotive, Aerospace, and Military Applications
by Sachin Kumar Sharma, Sandra Gajević, Lokesh Kumar Sharma, Reshab Pradhan, Yogesh Sharma, Ivan Miletić and Blaža Stojanović
Lubricants 2024, 12(12), 421; https://doi.org/10.3390/lubricants12120421 (registering DOI) - 29 Nov 2024
Abstract
Manufacturing sectors, including automotive, aerospace, military, and aviation, are paying close attention to the increasing need for composite materials with better characteristics. Composite materials are significantly used in industry owing to their high-quality, low-cost materials with outstanding characteristics and low weight. Hence, aluminum-based [...] Read more.
Manufacturing sectors, including automotive, aerospace, military, and aviation, are paying close attention to the increasing need for composite materials with better characteristics. Composite materials are significantly used in industry owing to their high-quality, low-cost materials with outstanding characteristics and low weight. Hence, aluminum-based materials are preferred over other traditional materials owing to their low cost, great wear resistance, and excellent strength-to-weight ratio. However, the mechanical characteristics and wear behavior of the Al-based materials can be further improved by using suitable reinforcing agents. The various reinforcing agents, including whiskers, particulates, continuous fibers, and discontinuous fibers, are widely used owing to enhanced tribological and mechanical behavior comparable to bare Al alloy. Further, the advancement in the overall characteristics of the composite material can be obtained by optimizing the process parameters of the processing approach and the amount and types of reinforcement. Amongst the various available techniques, stir casting is the most suitable technique for the manufacturing of composite material. The amount of reinforcement controls the porosity (%) of the composite, while the types of reinforcement identify the compatibility with Al alloy through improvement in the overall characteristics of the composites. Fly ash, SiC, TiC, Al2O3, TiO2, B4C, etc. are the most commonly used reinforcing agents in AMMCs (aluminum metal matrix composites). The current research emphasizes how different forms of reinforcement affect AMMCs and evaluates reinforcement influence on the mechanical and tribo characteristics of composite material. Full article
(This article belongs to the Special Issue Friction and Wear of Alloys)
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11 pages, 4463 KiB  
Article
Effect of Ga Doping on the Stability and Optoelectronic Properties of ZnSnO Thin Film Transistor
by Liang Guo, Qing Wang, Chao Wang, Xuefeng Chu, Yunpeng Hao, Yaodan Chi and Xiaotian Yang
Micromachines 2024, 15(12), 1445; https://doi.org/10.3390/mi15121445 (registering DOI) - 29 Nov 2024
Abstract
The electrical, stability and optoelectronic properties of GZTO TFTs with different Ga doping concentrations were investigated. Active layers were prepared by co-sputtering GaO and ZTO targets with different sputtering powers. The experimental results show that the surface of GZTO films is smooth, which [...] Read more.
The electrical, stability and optoelectronic properties of GZTO TFTs with different Ga doping concentrations were investigated. Active layers were prepared by co-sputtering GaO and ZTO targets with different sputtering powers. The experimental results show that the surface of GZTO films is smooth, which is favorable for stability. The off-state current is reduced by a factor of 10, the switching ratio is increased to 1.59 × 108, and the threshold voltage shift is reduced in PBS and NBS tests. In addition, the transmittance of all devices is greater than 80% in the visible range, and the optical bandgap of the TFTs is increased from 3.61 eV to 3.84 eV after Ga doping. The current enhancement of the GZTO TFTs is more pronounced under UV irradiation, with higher responsiveness and better-sustained photoconductivity. It is proved that Ga doped into ZTO as a carrier suppressor can better combine with oxygen vacancies and reduce the concentration of oxygen vacancies and oxygen defects compared with Zn and Sn atoms, thus improving stability. GaO, as a wide bandgap material, can improve the optical bandgap of GZTO TFTs so that they can better absorb the light in the UV wavelength band, and they can be used in the field of UV photodetection. Full article
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12 pages, 1408 KiB  
Review
The Role and Mechanism of Deubiquitinase USP7 in Tumor-Associated Inflammation
by Luhong Wang, Yong Zhang, Tao Yu and Huijian Wu
Biomedicines 2024, 12(12), 2734; https://doi.org/10.3390/biomedicines12122734 (registering DOI) - 29 Nov 2024
Abstract
Deubiquitinating enzymes are a class of proteases that remove ubiquitin tags from proteins, thereby controlling protein stability and function. Tumor inflammation arises from interactions between tumor cells and their microenvironment, which trigger an inflammatory response. The deubiquitinating enzyme USP7 plays a central role [...] Read more.
Deubiquitinating enzymes are a class of proteases that remove ubiquitin tags from proteins, thereby controlling protein stability and function. Tumor inflammation arises from interactions between tumor cells and their microenvironment, which trigger an inflammatory response. The deubiquitinating enzyme USP7 plays a central role in this process. Research suggests that USP7 may modulate various signaling pathways related to inflammatory responses through its deubiquitinating activity, thereby influencing tumor development and progression, including regulating T cell immune activity, improving macrophage anti-tumor activity, and regulating NF-κB signal pathways. Overall, describing the role and mechanism of USP7 in the tumor inflammatory response is of great importance for elucidating the regulatory mechanism of tumor inflammation and developing new therapeutic strategies. This article mainly reviews the structure, function, role, and mechanism of USP7 in the tumor inflammation response. Full article
(This article belongs to the Special Issue Ubiquitylation and Deubiquitylation in Health and Diseases)
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10 pages, 3222 KiB  
Article
MIF Inhibition by ISO-1 Decreased Autophagic Activity in Primary Astrocytes During Cobalt Chloride-Induced Hypoxia
by Ji-Hyun Park, Hye-Ji Cho, Dae-Yong Song, Jung-Ho Lee and Hong-Il Yoo
Curr. Issues Mol. Biol. 2024, 46(12), 13607-13616; https://doi.org/10.3390/cimb46120813 (registering DOI) - 29 Nov 2024
Abstract
Ischemic stroke is a leading contributor to death and disability worldwide, driving extensive research into pharmacological treatments beyond thrombolysis. Macrophage migration inhibitory factor (MIF), a cytokine, is implicated in several pathological conditions. In this study, we examined the effects of MIF on autophagy [...] Read more.
Ischemic stroke is a leading contributor to death and disability worldwide, driving extensive research into pharmacological treatments beyond thrombolysis. Macrophage migration inhibitory factor (MIF), a cytokine, is implicated in several pathological conditions. In this study, we examined the effects of MIF on autophagy in astrocytes under the condition of chemical hypoxia. Primary astrocytes were treated with cobalt chloride, a well-known drug for inducing chemical hypoxia, followed by Western blot analyses to assess the HIF-1α, MIF, and LC3 protein levels along with a CCK assay. Additionally, cobalt chloride-treated astrocytes were co-treated with the MIF inhibitor ISO-1, and Western blot analyses were performed for MIF and LC3. Cell viability was evaluated using the CCK assay in astrocytes treated with cobalt chloride and ISO-1, with additional rapamycin treatment. Our results show that ISO-1 reduced LC3-II levels in astrocytes exposed to high concentrations of cobalt chloride (1000 μM) for 6 h. Moreover, rapamycin decreased cell viability in astrocytes treated with both 1000 μM cobalt chloride and ISO-1. Our data suggest that MIF plays a role in inducing autophagy in astrocytes under hypoxic conditions and is involved in the regulation of autophagic activity. Full article
(This article belongs to the Special Issue Molecular Mechanisms and Treatment of Ischemia–Reperfusion Injury)
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16 pages, 2033 KiB  
Article
Intermittent Short Circuit Fault Location for CAN Based on Two-Port Network Modeling
by Longkai Wang, Yi Yang and Yong Lei
Actuators 2024, 13(12), 485; https://doi.org/10.3390/act13120485 (registering DOI) - 29 Nov 2024
Abstract
The Controller Area Network (CAN) has been adopted in various reliability-critical industrial systems. However, intermittent connection (IC) problems of network cables may worsen system performance and even threaten operational safety. Recently, there have been several studies on diagnosing intermittent open circuit faults, but [...] Read more.
The Controller Area Network (CAN) has been adopted in various reliability-critical industrial systems. However, intermittent connection (IC) problems of network cables may worsen system performance and even threaten operational safety. Recently, there have been several studies on diagnosing intermittent open circuit faults, but the intermittent short circuit (ISC) fault diagnosis has not been addressed. In this paper, a novel ISC fault location method for CANs is proposed based on two-port network modeling. First, the CAN network is modeled as a switched system that depends on the states of the sending nodes using a two-port network approach. An equivalent circuit model and a voltage transfer difference function (VTDF) group are derived for each state where one particular node is sending. Second, upon each fault, corresponding direction events are defined by comparing the two VTDF values that are calculated from the voltages collected at network ends. Then, the fault and health domains can be determined by integrating these direction events with the network topology information according to their statistical significance. Third, a bidirectional eviction localization algorithm is developed to identify ISC fault locations based on the fault and health domains. A testbed is constructed, and case studies are conducted to demonstrate that the proposed method can correctly locate the ISC faults in various network topological layouts. Full article
(This article belongs to the Section Control Systems)
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