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19 pages, 2243 KiB  
Article
Theoretical Calculation of Ground and Electronically Excited States of MgRb+ and SrRb+ Molecular Ions: Electronic Structure and Prospects of Photo-Association
by Mohamed Farjallah, Hela Ladjimi, Wissem Zrafi and Hamid Berriche
Atoms 2025, 13(8), 69; https://doi.org/10.3390/atoms13080069 - 25 Jul 2025
Abstract
In this work, a comprehensive theoretical investigation is carried out to explore the electronic and spectroscopic properties of selected diatomic molecular ions MgRb+ and SrRb+. Using high-level ab initio calculations based on a pseudopotential approach, along with large Gaussian basis [...] Read more.
In this work, a comprehensive theoretical investigation is carried out to explore the electronic and spectroscopic properties of selected diatomic molecular ions MgRb+ and SrRb+. Using high-level ab initio calculations based on a pseudopotential approach, along with large Gaussian basis sets and full valence configuration interaction (FCI), we accurately determine adiabatic potential energy curves, spectroscopic constants, transition dipole moments (TDMs), and permanent electric dipole moments (PDMs). To deepen our understanding of these systems, we calculate radiative lifetimes for vibrational levels in both ground and low-lying excited electronic states. This includes evaluating spontaneous and stimulated emission rates, as well as the effects of blackbody radiation. We also compute Franck–Condon factors and analyze photoassociation processes for both ions. Furthermore, to explore low-energy collisional dynamics, we investigate elastic scattering in the first excited states (21Σ+) describing the collision between the Ra atom and Mg+ or Sr+ ions. Our findings provide detailed insights into the theoretical electronic structure of these molecular ions, paving the way for future experimental studies in the field of cold and ultracold molecular ion physics. Full article
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16 pages, 1786 KiB  
Article
Repurposing Analysis of Nitroxoline (8-Hydroxy-5-nitroquinoline) as an Antichagasic Compound
by Carlos J. Bethencourt-Estrella, Atteneri López-Arencibia, Isabel M. Calero-Docina, Frieder Fuchs, Patrick Scheid, Jacob Lorenzo-Morales and José E. Piñero
Pharmaceuticals 2025, 18(8), 1106; https://doi.org/10.3390/ph18081106 - 25 Jul 2025
Abstract
Background/Objectives: Chagas disease, caused by the protozoan parasite Trypanosoma cruzi, remains a major neglected tropical disease, with over six million cases concentrated, primarily in Latin America. Despite decades of research, treatment continues to rely on two outdated drugs—benznidazole and nifurtimox—both of which [...] Read more.
Background/Objectives: Chagas disease, caused by the protozoan parasite Trypanosoma cruzi, remains a major neglected tropical disease, with over six million cases concentrated, primarily in Latin America. Despite decades of research, treatment continues to rely on two outdated drugs—benznidazole and nifurtimox—both of which exhibit limited efficacy and are associated with severe side effects. In this context, drug repurposing presents a promising strategy to accelerate the development of safer and more effective therapies. Nitroxoline, a hydroxyquinoline compound widely used in Europe to treat bacterial urinary tract infections, has recently garnered attention for its broad-spectrum antimicrobial and anticancer activities. This study evaluated the antitrypanosomal potential of nitroxoline against both epimastigote and intracellular amastigote forms of T. cruzi, demonstrating significantly greater efficacy than benznidazole. Methods: In addition to its antiparasitic activity, we investigated the mechanism of parasite death and found that nitroxoline induces hallmarks of programmed cell death, including chromatin condensation, mitochondrial membrane depolarization, ATP depletion, reactive oxygen species accumulation, and increased membrane permeability. These cellular events are critical for minimizing host tissue inflammation and suggest a safer therapeutic profile. Results: The nitroxoline was shown to induce greater activity than the reference treatment, benznidazole, in addition to triggering events related to apoptotic or silent cell death. Conclusions: Given its established clinical use and favorable safety data, nitroxoline emerges as a strong candidate for further investigation as a repurposed treatment for Chagas disease. Future work should focus on in vivo efficacy, pharmacokinetics, and drug delivery strategies to enhance systemic bioavailability. Full article
(This article belongs to the Special Issue Recent Advancements in the Development of Antiprotozoal Agents)
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34 pages, 2825 KiB  
Article
A Verilog Programming Learning Assistant System Focused on Basic Verilog with a Guided Learning Method
by Pin-Chieh Hsieh, Tzu-Lun Fang, Shaobo Jin, Yuyan Wang, Nobuo Funabiki and Yu-Cheng Fan
Future Internet 2025, 17(8), 333; https://doi.org/10.3390/fi17080333 - 25 Jul 2025
Abstract
With continuous advancements in semiconductor technology, mastering efficient designs of high-quality and advanced chips has become an important part of science and technology education. Chip performances will determine the futures of various aspects of societies. However, novice students often encounter difficulties in learning [...] Read more.
With continuous advancements in semiconductor technology, mastering efficient designs of high-quality and advanced chips has become an important part of science and technology education. Chip performances will determine the futures of various aspects of societies. However, novice students often encounter difficulties in learning digital chip designs using Verilog programming, a common hardware design language. An efficient self-study system for supporting them that can offer various exercise problems, such that any answer is marked automatically, is in strong demand. In this paper, we design and implement a web-based Verilog programming learning assistant system (VPLAS), based on our previous works on software programming. Using a heuristic and guided learning method, VPLAS leads students to learn the basic circuit syntax step by step, until they acquire high-quality digital integrated circuit design abilities through self-study. For evaluation, we assign the proposal to 50 undergraduate students at the National Taipei University of Technology, Taiwan, who are taking the introductory chip-design course, and confirm that their learning outcomes using VPLAS together are far better than those obtained when following a traditional method. In our final statistics, students achieved an average initial accuracy rate of over 70% on their first attempts at answering questions after learning through our website’s tutorials. With the help of the system’s instant automated grading and rapid feedback, their average accuracy rate eventually exceeded 99%. This clearly demonstrates that our system effectively enables students to independently master Verilog circuit knowledge through self-directed learning. Full article
(This article belongs to the Topic Advances in Online and Distance Learning)
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14 pages, 600 KiB  
Article
Farmer Apprenticeship: Working While Learning or Learning to Work? Experiences and Views on Farmer Apprenticeship in Contemporary Danish Animal Farming
by Mette Vaarst and Inger Anneberg
Agriculture 2025, 15(15), 1605; https://doi.org/10.3390/agriculture15151605 - 25 Jul 2025
Abstract
Agricultural education of future farmers includes a period of practice in Denmark. How can this be shaped to best support the education and future life as farmers? This question motivated a pilot study of how different factors influenced farmer apprentices’ learning in their [...] Read more.
Agricultural education of future farmers includes a period of practice in Denmark. How can this be shaped to best support the education and future life as farmers? This question motivated a pilot study of how different factors influenced farmer apprentices’ learning in their on-farm apprentice period, based on interviews of farmer students and host farmers, and to explore this in the historical and social context of Danish agriculture. Three focus group interviews with 24 farmer apprentices were conducted, as well as 14 qualitative semi-structured phone interviews with host farmers. Four major themes emerged from the interviews with host farmers and apprentices: There is a potential conflict between the two perspectives in themes one and two: The host farm primarily as a learning site, versus the apprentice being primarily a farm laborer learning through working on the host farm as a workplace. Thirdly, the on-farm and social environment was suggested to have significant importance for developing into a future farmer, which resonates with the concept of Communities of Practice (CoP). This pilot study raised important issues regarding how future farmers are motivated and educated, highlighting that agricultural colleges play a pivotal role in articulating and guiding how the apprentice learning on-farm can be meaningfully integrated into the other parts of the farmer education. Full article
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
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23 pages, 2380 KiB  
Article
DEEPEIA: Conceptualizing a Generative Deep Learning Foreign Market Recommender for SMEs
by Nuno Calheiros-Lobo, Manuel Au-Yong-Oliveira and José Vasconcelos Ferreira
Information 2025, 16(8), 636; https://doi.org/10.3390/info16080636 - 25 Jul 2025
Abstract
This study introduces the concept of DEEPEIA, a novel deep learning (DL) platform designed to recommend the optimal export market, and its ideal foreign champion, for any product or service offered by a small and medium-sized enterprise (SME). Drawing on expertise in SME [...] Read more.
This study introduces the concept of DEEPEIA, a novel deep learning (DL) platform designed to recommend the optimal export market, and its ideal foreign champion, for any product or service offered by a small and medium-sized enterprise (SME). Drawing on expertise in SME internationalization and leveraging recent advances in generative artificial intelligence (AI), this research addresses key challenges faced by SMEs in global expansion. A systematic review of existing platforms was conducted to identify current gaps and inform the conceptualization of an advanced generative DL recommender system. The Discussion section proposes the conceptual framework for such a decision optimizer within the context of contemporary technological advancements and actionable insights. The conclusion outlines future research directions, practical implementation strategies, and expected obstacles. By mapping the current landscape and presenting an original forecasting tool, this work advances the field of AI-enabled SME internationalization while still acknowledging that more empirical validation remains a necessary next step. Full article
(This article belongs to the Special Issue Artificial Intelligence (AI) for Economics and Business Management)
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11 pages, 404 KiB  
Article
Nutrient Concentration in Leaves, Branches, and Reproductive Organs of Coffea canephora Genotypes in Three Phenophases
by Maria Juliete Lucindo Rodrigues, Larícia Olária Emerick Silva, Ivoney Gontijo, Henrique Duarte Vieira, Alexandre Pio Viana, Miroslava Rakocevic and Fábio Luiz Partelli
Horticulturae 2025, 11(8), 872; https://doi.org/10.3390/horticulturae11080872 - 25 Jul 2025
Abstract
The nutrient requirements of coffee plants vary according to their phenological stages, with each nutrient playing specific roles in different structures and developmental phases. This study evaluated dry matter accumulation and the concentrations of N, P, K, Ca, Mg, S, Fe, Mn, Cu, [...] Read more.
The nutrient requirements of coffee plants vary according to their phenological stages, with each nutrient playing specific roles in different structures and developmental phases. This study evaluated dry matter accumulation and the concentrations of N, P, K, Ca, Mg, S, Fe, Mn, Cu, Zn, and B in the leaves, branches, and reproductive organs of five Coffea canephora genotypes during three phenophases: flowering, fruit development, and fruit ripening. This work aimed to evaluate the distribution of nutrients in three phenophases in Coffeea canephora genotypes. Significant differences were observed among genotypes and phenophases. During flowering, leaves accumulated the highest amount of dry matter, but this pattern reversed in later stages, with greater accumulation in the fruits, especially during fruit ripening. The Verdim TA genotype showed the lowest dry matter accumulation in the branches across all phenophases. Genotypes A1 and Clementino presented the highest mean concentrations of P, Ca, Mg, Fe, Cu, and Zn in the leaves during the fruit development phase, while Verdim TA showed the lowest concentrations of P, K, Ca, Mn, Zn, and B. Future studies may include additional phenological stages and quantify nutrient remobilization efficiency in each genotype, contributing to improved management recommendation. Full article
(This article belongs to the Special Issue Mineral Nutrition of Plants)
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23 pages, 2406 KiB  
Review
Current Research on Quantifying Cotton Yield Responses to Waterlogging Stress: Indicators and Yield Vulnerability
by Long Qian, Yunying Luo and Kai Duan
Plants 2025, 14(15), 2293; https://doi.org/10.3390/plants14152293 - 25 Jul 2025
Abstract
Cotton (Gossypium spp.) is an important industrial crop, but it is vulnerable to waterlogging stress. The relationship between cotton yields and waterlogging indicators (CY-WI) is fundamental for waterlogging disaster reduction. This review systematically summarized and analyzed literature containing CY-WI relations across 1970s–2020s. [...] Read more.
Cotton (Gossypium spp.) is an important industrial crop, but it is vulnerable to waterlogging stress. The relationship between cotton yields and waterlogging indicators (CY-WI) is fundamental for waterlogging disaster reduction. This review systematically summarized and analyzed literature containing CY-WI relations across 1970s–2020s. China conducted the most CY-WI experiments (67%), followed by Australia (17%). Recent decades (2010s, 2000s) contributed the highest proportion of CY-WI works (49%, 15%). Surface waterlogging form is mostly employed (74%) much more than sub-surface waterlogging. The flowering and boll-forming stage, followed by the budding stage, performed the most CY-WI experiments (55%), and they showed stronger negative relations of CY-WI than other stages. Some compound stresses enhance negative relations of CY-WI, such as accompanying high temperatures, low temperatures, and shade conditions, whereas some others weaken the negative CY-WI relations, such as prior/post drought and waterlogging. Anti-waterlogging applications significantly weaken negative CY-WI relations. Regional-scale CY-WI research is increasing now, and they verified the influence of compound stresses. In future CI-WI works, we should emphasize the influence of compound stresses, establish regional CY-WI relations regarding cotton growth features, examine more updated cotton cultivars, focus on initial and late cotton stages, and explore the consequence of high-deep submergence. Full article
(This article belongs to the Section Plant Response to Abiotic Stress and Climate Change)
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15 pages, 2264 KiB  
Article
SimpleScale: Simplifying the Training of an LLM Model Using 1024 GPUs
by Tianfa Li, Jingshan Pan, Siwei Ma, Aleksandr Raikov and Alexander Arkhipov
Appl. Sci. 2025, 15(15), 8265; https://doi.org/10.3390/app15158265 - 25 Jul 2025
Abstract
LLMs are trained using many thousands of GPUs in well-known conventional models. It is necessary to address numerous issues in the training process, such as manual data collection organization, data parallel, model parallel, evaluation, testing, deployment, transferring large data streams, detecting errors, ongoing [...] Read more.
LLMs are trained using many thousands of GPUs in well-known conventional models. It is necessary to address numerous issues in the training process, such as manual data collection organization, data parallel, model parallel, evaluation, testing, deployment, transferring large data streams, detecting errors, ongoing maintenance, and project management. A team of dozens of engineers is required to handle system problems in the training process. Therefore, it is time-consuming and expensive to build an efficient and fault-tolerant system based on Kubernetes. This paper develops SimpleScale for building LLMs based on FSDP and Slurm, which is a simple and efficient training system that includes the training agent, the efficient parallel strategy, the optimal step of checkpoint, and so on. Using the proposed system enables us to significantly accelerate the process of building the LLM without incurring substantial time spent on various manual issues. The proposed 1024-GPU cluster was tested on TinyLlama, which has 1.1 billion parameters and 300 billion tokens. For example, utilizing a 16-H100 GPU cluster accelerated the traditional TinyLlama training time costs from 89.05 days to 39.05 days. In the future, the project team plans to integrate Flash-Attention3, aiming for an MFU of more than 60% while maintaining the acceleration achieved in the present work. Full article
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15 pages, 6406 KiB  
Communication
Design and Static Analysis of MEMS-Actuated Silicon Nitride Waveguide Optical Switch
by Yan Xu, Tsen-Hwang Andrew Lin and Peiguang Yan
Micromachines 2025, 16(8), 854; https://doi.org/10.3390/mi16080854 - 25 Jul 2025
Abstract
This article aims to utilize a microelectromechanical system (MEMS) to modulate coupling behavior of silicon nitride (Si3N4) waveguides to perform an optical switch based on a directional coupling (DC) mechanism. There are two states of the switch. First state, [...] Read more.
This article aims to utilize a microelectromechanical system (MEMS) to modulate coupling behavior of silicon nitride (Si3N4) waveguides to perform an optical switch based on a directional coupling (DC) mechanism. There are two states of the switch. First state, a Si3N4 wire is initially positioned up suspended in the air. In the second state, this wire will be moved down to be placed between two arms of the DC waveguides, changing the coupling behavior to achieve bar and cross states of the optical switch function. In the future, the MEMS will be used to move this wire down. In this work, we present simulations of the two static states to optimize the DC structure parameters. Based on the simulated results, the device size is 8.8 μm × 55 μm. The insertion loss is calculated to be approximately 0.24 dB and 0.33 dB, the extinction ratio is approximately 24.70 dB and 25.46 dB, and the crosstalk is approximately −24.60 dB and −25.56 dB, respectively. In the C band of optical communication, the insertion loss ranges from 0.18 dB to 0.47 dB. As such, this device will exhibit excellent optical switch performance and provide advantages in many integrated optics-related optical systems applications. Furthermore, it can be used in optical communications, data centers, LiDAR, and so on, enhancing important reference value for such applications. Full article
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20 pages, 3116 KiB  
Article
Deep Learning for Visual Leading of Ships: AI for Human Factor Accident Prevention
by Manuel Vázquez Neira, Genaro Cao Feijóo, Blanca Sánchez Fernández and José A. Orosa
Appl. Sci. 2025, 15(15), 8261; https://doi.org/10.3390/app15158261 - 24 Jul 2025
Abstract
Traditional navigation relies on visual alignment with leading lights, a task typically monitored by bridge officers over extended periods. This process can lead to fatigue-related human factor errors, increasing the risk of maritime accidents and environmental damage. To address this issue, this study [...] Read more.
Traditional navigation relies on visual alignment with leading lights, a task typically monitored by bridge officers over extended periods. This process can lead to fatigue-related human factor errors, increasing the risk of maritime accidents and environmental damage. To address this issue, this study explores the use of convolutional neural networks (CNNs), evaluating different training strategies and hyperparameter configurations to assist officers in identifying deviations from proper visual leading. Using video data captured from a navigation simulator, we trained a lightweight CNN capable of advising bridge personnel with an accuracy of 86% during night-time operations. Notably, the model demonstrated robustness against visual interference from other light sources, such as lighthouses or coastal lights. The primary source of classification error was linked to images with low bow deviation, largely influenced by human mislabeling during dataset preparation. Future work will focus on refining the classification scheme to enhance model performance. We (1) propose a lightweight CNN based on SqueezeNet for night-time ship navigation, (2) expand the traditional binary risk classification into six operational categories, and (3) demonstrate improved performance over human judgment in visually ambiguous conditions. Full article
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13 pages, 321 KiB  
Article
Male Coal Miners’ Shared Work Crew Identity and Their Safety Behavior: A Multilevel Mediation Analysis
by Zhen Hu, Siyi Li, Yuzhong Shen, Changquan He, Carol K. H. Hon and Zhizhou Xu
Sustainability 2025, 17(15), 6762; https://doi.org/10.3390/su17156762 - 24 Jul 2025
Abstract
Coal miners’ unsafe behavior is the primary reason for accidents. This research aims to examine the effect of male coal miners’ shared work crew identity on their safety behavior. A 2-2-1 multilevel mediation model is established based on social identity theory and safety [...] Read more.
Coal miners’ unsafe behavior is the primary reason for accidents. This research aims to examine the effect of male coal miners’ shared work crew identity on their safety behavior. A 2-2-1 multilevel mediation model is established based on social identity theory and safety climate theory. To validate the model, a paper-and-pencil survey with male coal miners was carried out in Henan Province, China. A total of 212 valid responses from male coal miners nested in 53 work crews were secured, and Mplus was used to analyze the data. Results show that work crew safety climate fully mediates the effect of male coal miners’ shared work crew identity on their safety behavior. In theory, the findings support that social identity brings a safety climate. In practice, the findings highlight that making safety part of work crew norms improves male coal miners’ safety behavior. Limitations and future research are also discussed. Full article
(This article belongs to the Special Issue Human Behavior, Psychology and Sustainable Well-Being: 2nd Edition)
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17 pages, 13125 KiB  
Article
Evaluating the Accuracy and Repeatability of Mobile 3D Imaging Applications for Breast Phantom Reconstruction
by Elena Botti, Bart Jansen, Felipe Ballen-Moreno, Ayush Kapila and Redona Brahimetaj
Sensors 2025, 25(15), 4596; https://doi.org/10.3390/s25154596 - 24 Jul 2025
Abstract
Three-dimensional imaging technologies are increasingly used in breast reconstructive and plastic surgery due to their potential for efficient and accurate preoperative assessment and planning. This study systematically evaluates the accuracy and consistency of six commercially available 3D scanning applications (apps)—Structure Sensor, 3D Scanner [...] Read more.
Three-dimensional imaging technologies are increasingly used in breast reconstructive and plastic surgery due to their potential for efficient and accurate preoperative assessment and planning. This study systematically evaluates the accuracy and consistency of six commercially available 3D scanning applications (apps)—Structure Sensor, 3D Scanner App, Heges, Polycam, SureScan, and Kiri—in reconstructing the female torso. To avoid variability introduced by human subjects, a silicone breast mannequin model was scanned, with fiducial markers placed at known anatomical landmarks. Manual distance measurements were obtained using calipers by two independent evaluators and compared to digital measurements extracted from 3D reconstructions in Blender software. Each scan was repeated six times per application to ensure reliability. SureScan demonstrated the lowest mean error (2.9 mm), followed by Structure Sensor (3.0 mm), Heges (3.6 mm), 3D Scanner App (4.4 mm), Kiri (5.0 mm), and Polycam (21.4 mm), which showed the highest error and variability. Even the app using an external depth sensor (Structure Sensor) showed no statistically significant accuracy advantage over those using only the iPad’s built-in camera (except for Polycam), underscoring that software is the primary driver of performance, not hardware (alone). This work provides practical insights for selecting mobile 3D scanning tools in clinical workflows and highlights key limitations, such as scaling errors and alignment artifacts. Future work should include patient-based validation and explore deep learning to enhance reconstruction quality. Ultimately, this study lays the foundation for more accessible and cost-effective 3D imaging in surgical practice, showing that smartphone-based tools can produce clinically useful scans. Full article
(This article belongs to the Special Issue Biomedical Imaging, Sensing and Signal Processing)
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15 pages, 2636 KiB  
Article
Chest Compression Skill Evaluation System Using Pose Estimation and Web-Based Application
by Ryota Watanabe, Jahidul Islam, Xin Zhu, Emiko Kaneko, Ken Iseki and Lei Jing
Appl. Sci. 2025, 15(15), 8252; https://doi.org/10.3390/app15158252 - 24 Jul 2025
Abstract
It is critical to provide life-sustaining treatment to OHCA patients before ambulance care arrives. However, incorrectly performed resuscitation maneuvers reduce the chances of survival and recovery for the victims. Therefore, we must train regularly and learn how to do it correctly. To facilitate [...] Read more.
It is critical to provide life-sustaining treatment to OHCA patients before ambulance care arrives. However, incorrectly performed resuscitation maneuvers reduce the chances of survival and recovery for the victims. Therefore, we must train regularly and learn how to do it correctly. To facilitate regular chest compression training, this study aims to improve the accuracy of a chest compression evaluation system using posture estimation and to develop a web application. To analyze and enhance accuracy, the YOLOv8 posture estimation was used to examine compression depth, recoil, and tempo, and its accuracy was compared to that of the manikin, which has evaluation systems. We conducted comparative experiments with different camera angles and heights to optimize the accuracy of the evaluation. The experimental results showed that an angle of 30 degrees and a height of 50 cm produced superior accuracy. For web application development, a system has been designed to allow users to upload videos for analysis and obtain appropriate compression parameters. The usability evaluation of the application confirmed its ease of use and accessibility, and positive feedback was obtained. In the conclusion, these findings suggest that optimizing recording conditions significantly improves the accuracy of posture-based chest compression evaluation. Future work will focus on enhancing real-time feedback functionality and improving the user interface of the web application. Full article
(This article belongs to the Special Issue Machine Learning in Biomedical Applications)
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27 pages, 3560 KiB  
Review
Antimicrobial Potential of Nanomaterials Synthesized with Extracts from Annona Plants: A Review
by Yared Gutiérrez-Pinzón, Alma Hortensia Martínez-Preciado, José Miguel Velázquez-López, Cristina Pech-Jiménez, Víctor Manuel Zúñiga-Mayo, Santiago José Guevara-Martínez and Gilberto Velázquez-Juárez
Antibiotics 2025, 14(8), 748; https://doi.org/10.3390/antibiotics14080748 - 24 Jul 2025
Abstract
Plants of the Annona genus have garnered increasing scientific interest due to their rich phytochemical profile and broad spectrum of biological activities, which include antimicrobial, antiproliferative, and cytotoxic effects. Among the most studied compounds are acetogenins and Annonacins, which exhibit potent bioactivity [...] Read more.
Plants of the Annona genus have garnered increasing scientific interest due to their rich phytochemical profile and broad spectrum of biological activities, which include antimicrobial, antiproliferative, and cytotoxic effects. Among the most studied compounds are acetogenins and Annonacins, which exhibit potent bioactivity and have been identified as key agents in the green synthesis and stabilization of nanomaterials. In recent years, the integration of Annona plant extracts—particularly from leaves—into nanotechnology platforms has opened new avenues in the development of eco-friendly and biocompatible nanostructures for biomedical applications. This review provides a comprehensive overview of the current knowledge regarding the antimicrobial properties of nanomaterials synthesized using extracts from Annona species. This review encompasses 74 indexed articles published between 2012 and 2023, focusing on the synthesis of nanomaterials using extracts from this genus that exhibit antimicrobial and biomedical properties. The search was conducted in databases such as Google Scholar, Web of Science, and Scopus. Emphasis is placed on their antibacterial, antifungal, and anthelmintic effects, as well as additional therapeutic potentials, such as antidiabetic, antihypertensive, antiproliferative, and cytotoxic activities. The analysis of the recent literature highlights how Annona-derived phytochemicals contribute significantly to the functionalization and enhanced biological performance of these nanomaterials. This work aims to support future research focused on the rational design of Annona-based nanostructures as promising candidates in antimicrobial and therapeutic strategies. Full article
(This article belongs to the Special Issue Antimicrobial Activity of Secondary Metabolites Produced in Nature)
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25 pages, 4040 KiB  
Review
Progress in Electrode Materials for the Detection of Nitrofurazone and Nitrofurantoin
by Mohammad Aslam, Saood Ali, Khursheed Ahmad and Danishuddin
Biosensors 2025, 15(8), 482; https://doi.org/10.3390/bios15080482 - 24 Jul 2025
Abstract
Recently, it has been found that electrochemical sensing technology is one of the significant approaches for the monitoring of toxic and hazardous substances in food and the environment. Nitrofurazone (NFZ) and nitrofurantoin (NFT) possess a hazardous influence on the environment, aquatic life, and [...] Read more.
Recently, it has been found that electrochemical sensing technology is one of the significant approaches for the monitoring of toxic and hazardous substances in food and the environment. Nitrofurazone (NFZ) and nitrofurantoin (NFT) possess a hazardous influence on the environment, aquatic life, and human health. Thus, various advanced materials such as graphene, carbon nanotubes, metal oxides, MXenes, layered double hydroxides (LDHs), polymers, metal–organic frameworks (MOFs), metal-based composites, etc. are widely used for the development of nitrofurazone and nitrofurantoin sensors. This review article summarizes the progress in the fabrication of electrode materials for nitrofurazone and nitrofurantoin sensing applications. The performance of the various electrode materials for nitrofurazone and nitrofurantoin monitoring are discussed. Various electrochemical sensing techniques such as square wave voltammetry (SWV), differential pulse voltammetry (DPV), linear sweep voltammetry (LSV), amperometry (AMP), cyclic voltammetry (CV), and chronoamperometry (CA) are discussed for the determination of NFZ and NFT. It is observed that DPV, SWV, and AMP/CA are more sensitive techniques compared to LSV and CV. The challenges, future perspectives, and limitations of NFZ and NFT sensors are also discussed. It is believed that present article may be useful for electrochemists as well materials scientists who are working to design electrode materials for electrochemical sensing applications. Full article
(This article belongs to the Special Issue Advanced Nanomaterials for Electrochemical Biosensing Application)
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