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20 pages, 688 KiB  
Article
Multi-Modal AI for Multi-Label Retinal Disease Prediction Using OCT and Fundus Images: A Hybrid Approach
by Amina Zedadra, Mahmoud Yassine Salah-Salah, Ouarda Zedadra and Antonio Guerrieri
Sensors 2025, 25(14), 4492; https://doi.org/10.3390/s25144492 - 19 Jul 2025
Viewed by 480
Abstract
Ocular diseases can significantly affect vision and overall quality of life, with diagnosis often being time-consuming and dependent on expert interpretation. While previous computer-aided diagnostic systems have focused primarily on medical imaging, this paper proposes VisionTrack, a multi-modal AI system for predicting multiple [...] Read more.
Ocular diseases can significantly affect vision and overall quality of life, with diagnosis often being time-consuming and dependent on expert interpretation. While previous computer-aided diagnostic systems have focused primarily on medical imaging, this paper proposes VisionTrack, a multi-modal AI system for predicting multiple retinal diseases, including Diabetic Retinopathy (DR), Age-related Macular Degeneration (AMD), Diabetic Macular Edema (DME), drusen, Central Serous Retinopathy (CSR), and Macular Hole (MH), as well as normal cases. The proposed framework integrates a Convolutional Neural Network (CNN) for image-based feature extraction, a Graph Neural Network (GNN) to model complex relationships among clinical risk factors, and a Large Language Model (LLM) to process patient medical reports. By leveraging diverse data sources, VisionTrack improves prediction accuracy and offers a more comprehensive assessment of retinal health. Experimental results demonstrate the effectiveness of this hybrid system, highlighting its potential for early detection, risk assessment, and personalized ophthalmic care. Experiments were conducted using two publicly available datasets, RetinalOCT and RFMID, which provide diverse retinal imaging modalities: OCT images and fundus images, respectively. The proposed multi-modal AI system demonstrated strong performance in multi-label disease prediction. On the RetinalOCT dataset, the model achieved an accuracy of 0.980, F1-score of 0.979, recall of 0.978, and precision of 0.979. Similarly, on the RFMID dataset, it reached an accuracy of 0.989, F1-score of 0.881, recall of 0.866, and precision of 0.897. These results confirm the robustness, reliability, and generalization capability of the proposed approach across different imaging modalities. Full article
(This article belongs to the Section Sensing and Imaging)
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9 pages, 1297 KiB  
Communication
Near-Infrared Emitting Chiral Tetranuclear Erbium Cluster Containing Soft-Base Bisthiazolate Linkers
by Vasily A. Ilichev, Anton F. Rogozhin, Roman V. Rumyantcev, Georgy K. Fukin and Mikhail N. Bochkarev
Molbank 2025, 2025(2), M2015; https://doi.org/10.3390/M2015 - 29 May 2025
Viewed by 1144
Abstract
A tetraerbium cluster containing soft-base dianionic 4,8-difluorobenzo [1,2-d:5,4-d′]bisthiazole-2,6-dithiol (H2L) ligands, μ-OH, and coordinated 1,2-dimethoxyethane (DME) of the general formula {Er4(μ-L)4(μ-OH)4(DME)4} (1) was synthesized using [...] Read more.
A tetraerbium cluster containing soft-base dianionic 4,8-difluorobenzo [1,2-d:5,4-d′]bisthiazole-2,6-dithiol (H2L) ligands, μ-OH, and coordinated 1,2-dimethoxyethane (DME) of the general formula {Er4(μ-L)4(μ-OH)4(DME)4} (1) was synthesized using a one-pot method. X-ray analysis revealed that 1 is an asymmetrical tetramer in which there are four μ2-bridging bisthiazole ligands and four μ2-bridging hydroxide anions per four erbium ions. The molecule of 1 has inherent chirality, and the geometry of intramolecular F…F short contacts implies the formation of a classical halogen bond. Upon excitation by a 375 nm diode laser, compound 1 shows the moderate metal-centered emission of Er3+ ions that peaked at 1530 nm. Full article
(This article belongs to the Section Structure Determination)
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26 pages, 4267 KiB  
Review
Ammonia-Based Clean Energy Systems: A Review of Recent Progress and Key Challenges
by Mengwei Sun, Zhongqian Ling, Jiani Mao, Xianyang Zeng, Dingkun Yuan and Maosheng Liu
Energies 2025, 18(11), 2845; https://doi.org/10.3390/en18112845 - 29 May 2025
Viewed by 857
Abstract
Ammonia is gaining increasing attention as a zero-carbon fuel and hydrogen carrier, offering high energy density, mature liquefaction infrastructure, and strong compatibility with existing energy systems. This review presents a comprehensive summary of the recent advances in ammonia-based clean energy systems. It covers [...] Read more.
Ammonia is gaining increasing attention as a zero-carbon fuel and hydrogen carrier, offering high energy density, mature liquefaction infrastructure, and strong compatibility with existing energy systems. This review presents a comprehensive summary of the recent advances in ammonia-based clean energy systems. It covers the fuel’s physicochemical properties, green synthesis pathways, storage and transport technologies, combustion behavior, NOX formation mechanisms, emission control strategies, and safety considerations. Co-firing approaches with hydrogen, methane, coal, and DME are evaluated to address ammonia’s low reactivity and narrow flammability limits. This paper further reviews engineering applications across power generation, maritime propulsion, and long-duration energy storage, drawing insights from current demonstration projects. Key technical barriers—including ignition delay, NOX emissions, ammonia slip, and economic feasibility—are critically examined. Finally, future development trends are discussed, highlighting the importance of integrated system design, low-NOX combustor development, solid-state storage materials, and supportive policy frameworks. Ammonia is expected to serve as a strategic energy vector bridging green hydrogen production with zero-carbon end-use, facilitating the transition to a sustainable, secure, and flexible energy future. Full article
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13 pages, 1146 KiB  
Article
Predictive Value of Optical Coherence Tomography Biomarkers in Patients with Persistent Diabetic Macular Edema Undergoing Cataract Surgery Combined with a Dexamethasone Intravitreal Implant
by Giuseppe Fasolino, Maryam Lazaar, Domenico Giovanni Della Rocca, Silke Oellerich and Sorcha Ní Dhubhghaill
Bioengineering 2025, 12(5), 556; https://doi.org/10.3390/bioengineering12050556 - 21 May 2025
Cited by 1 | Viewed by 744
Abstract
Background: Diabetic macular edema (DME) is the most common cause of vision loss among diabetic patients. The first-line treatments for DME are anti-vascular endothelial growth factor (VEGF)-drugs, while intravitreal steroids are generally reserved for second-line treatment. Limited data exist on the role of [...] Read more.
Background: Diabetic macular edema (DME) is the most common cause of vision loss among diabetic patients. The first-line treatments for DME are anti-vascular endothelial growth factor (VEGF)-drugs, while intravitreal steroids are generally reserved for second-line treatment. Limited data exist on the role of optical coherence tomography (OCT) biomarkers as predictors of success in non-responders to anti-VEGF treatment undergoing simultaneous cataract surgery and dexamethasone intravitreal implant (DEX-I). Methods: This study was designed as a retrospective analysis of patients with DME who were refractory to anti-VEGF treatment but underwent cataract surgery and received a DEX-I at the time of surgery. All procedures were performed between May 2021 and February 2024. The best-corrected visual acuity (BCVA) and central subfoveal thickness (CST) were recorded at baseline and at 1 week, 1 month, and 3 months. The following OCT-based biomarkers were also collected: ellipsoid zone (EZ) integrity, disorganization of the retinal inner layers (DRIL), CST, and hyperreflective foci (HRF). Correlations between the baseline biomarkers and the anatomical outcome were analyzed using linear mixed models (LMMs). Results: Eleven patients (eighteen eyes) met the inclusion criteria. The mean CST decreased significantly from 469.4 ± 53.8 µm at baseline, to 373.1 ± 34.7 µm at 1 week (p = 0.002) and 354.4 ± 24.1 µm at 1 month (p = 0.011). The mean BCVA improved significantly from 0.47 LogMAR to 0.33 LogMAR at 1 week (p = 0.001), 0.23 LogMAR at 1 month (p < 0.001), and 0.25 LogMAR at 3 months (p < 0.001). Baseline predictors significantly influencing CST included the presence of DRIL, a disrupted/absent EZ, and a higher CST. Conclusions: The administration of DEX-I for DME refractory to anti-VEGF treatment in patients undergoing cataract surgery promoted functional improvements persisting longer than the anatomical ones. Patients presenting with DRIL, disrupted EZ, and higher CST at baseline may be better candidates for the combination of DEX-I and cataract surgery. Full article
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17 pages, 3103 KiB  
Article
Design and Simulation of an Integrated Process for the Co-Production of Power, Hydrogen, and DME by Using an Electrolyzer’s System
by Asmae Abousalmia and Seckin Karagoz
Energies 2025, 18(10), 2446; https://doi.org/10.3390/en18102446 - 10 May 2025
Viewed by 523
Abstract
The increasing global demand for clean energy and sustainable industrial processes necessitates innovative approaches to energy production and chemical synthesis. This study proposed and simulated an innovative integrated system for the co-production of power, hydrogen, and dimethyl ether (DME), combining the high-efficiency Allam–Fetvedt [...] Read more.
The increasing global demand for clean energy and sustainable industrial processes necessitates innovative approaches to energy production and chemical synthesis. This study proposed and simulated an innovative integrated system for the co-production of power, hydrogen, and dimethyl ether (DME), combining the high-efficiency Allam–Fetvedt cycle with co-electrolysis and indirect DME synthesis. The Allam–Fetvedt cycle generated electricity while capturing CO2, which, along with water, was used in solid oxide electrolyzers (SOEs) to produce syngas via co-electrolysis. The resulting syngas was converted to methanol and subsequently to DME. Aspen HYSYS was used to model and simulate the process, and heat/mass integration strategies were implemented to reduce energy demand and optimize resource utilization. The proposed integrated process enabled an annual production of 980,021 metric tons of DME, 189,435 metric tons of hydrogen, and 7698.27 metric tons of methanol. The energy efficiency of the Allam–Fetvedt cycle reached 55%, and heat integration reduced the system’s net energy demand by 14.22%. Despite the high energy needs of the electrolyzer system (81.28% of net energy), the overall energy requirement remained competitive with conventional methods. Carbon emissions per kilogram of DME were reduced from 1.16 to 0.77 kg CO2 through heat integration and can be further minimized to 0.0308 kg CO2/kg DME (near zero) with renewable electrification. Results demonstrated that 96% of CO2 was recycled within the Allam–Fetvedt cycle, and the rest (the 4% of CO2) was captured and converted to syngas, achieving net-zero carbon emissions. This work presents a scalable and sustainable pathway for integrated clean energy and chemical production, advancing toward industrial net-zero targets. Full article
(This article belongs to the Special Issue Renewable Fuels: A Key Step Towards Global Sustainability)
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13 pages, 1322 KiB  
Article
The Association of Delayed Milk Ejection and Milk Production in Dairy Cows Milked by an Automated Milking System
by Matthias Wieland and Heleen ten Have
Animals 2025, 15(7), 1011; https://doi.org/10.3390/ani15071011 - 31 Mar 2025
Cited by 1 | Viewed by 562
Abstract
This retrospective cohort study examined the association between delayed milk ejection (DME), defined as bimodal milk flow, and milk yield in dairy cows milked with an automated milking system (AMS). Additionally, we identified risk factors for DME. Using data from a farm milking [...] Read more.
This retrospective cohort study examined the association between delayed milk ejection (DME), defined as bimodal milk flow, and milk yield in dairy cows milked with an automated milking system (AMS). Additionally, we identified risk factors for DME. Using data from a farm milking approximately 1350 cows, we analyzed 689,484 individual milking records and 194,142 daily cow observations over 350 days with generalized linear mixed models. Cows with DME generally had higher daily milk yields, regardless of lactation number. However, first-lactation cows early in lactation and older cows (≥third lactation) late in lactation produced less milk when experiencing DME. In contrast to the higher daily milk yield, cows produced less milk per milking when experiencing delayed milk ejection. However, more frequent milkings contributed to higher daily milk yield, even with more instances of delayed milk ejection. Risk factors for DME included lactation number, stage of lactation, milking frequency, and milking interval. These findings underscore the complexity of DME in AMS and suggest that optimizing individualized milking protocols could improve milk yield efficiency. Understanding the interplay of cow characteristics and milking management may enhance AMS performance and dairy herd productivity. Full article
(This article belongs to the Section Cattle)
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17 pages, 4113 KiB  
Article
The Adaptation of MCF-7 Breast Cancer Spheroids to the Chemotherapeutic Doxorubicin: The Dynamic Role of Phase I Drug Metabolizing Enzymes
by Daniel Crispim, Carolina Ramos, Francisco Esteves and Michel Kranendonk
Metabolites 2025, 15(2), 136; https://doi.org/10.3390/metabo15020136 - 18 Feb 2025
Viewed by 1505
Abstract
Background/Objectives: Drug resistance (DR) is a major challenge in cancer therapy, contributing to approximately 90% of cancer-related deaths. While alterations in drug metabolism are known to be key drivers of DR, their role—particularly in the early stages of acquired chemoresistance—remains understudied. Phase I [...] Read more.
Background/Objectives: Drug resistance (DR) is a major challenge in cancer therapy, contributing to approximately 90% of cancer-related deaths. While alterations in drug metabolism are known to be key drivers of DR, their role—particularly in the early stages of acquired chemoresistance—remains understudied. Phase I drug-metabolizing enzymes (DMEs), especially cytochrome P450s (CYPs), significantly influence the metabolic fate of chemotherapeutic agents, directly affecting drug response. This study aimed to investigate the role of Phase I DMEs in the early metabolic adaptation of breast cancer (BC) MCF-7 cells to doxorubicin (DOX). Methods: Four types of spheroids were generated from MCF-7 cells that were either DOX-sensitive (DOXS) or adapted to low concentrations of the chemotherapeutic agent (DOXA 25, 35, and 45 nM). The expression levels of 92 Phase I DMEs and the activities of specific CYP isoforms were assessed in both DOXS and DOXA spheroids. Results: A total of twenty-four DMEs, including fifteen CYPs and nine oxidoreductases, were found to be differentially expressed in DOXA spheroids. Pathway analysis identified key roles for the differentially expressed DMEs in physiologically relevant pathways, including the metabolism of drugs, arachidonic acid, retinoic acid, and vitamin D. Conclusions: The deconvolution of these pathways highlights a highly dynamic process driving early-stage DOX resistance, with a prominent role of CYP3A-dependent metabolism in DOX adaptation. Our findings provide valuable insights into the underlying molecular mechanisms driving the early adaptation of MCF-7 cells to DOX exposure. Full article
(This article belongs to the Special Issue Drug Metabolism: Latest Advances and Prospects)
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19 pages, 2671 KiB  
Article
Reproductive Potential and Population Growth of the Worm Enchytraeus buchholzi (Clitellata: Enchytraeidae) Under Laboratory Conditions as Well as Regression Models
by Limin Zhao and Guilan Ma
Biology 2025, 14(2), 167; https://doi.org/10.3390/biology14020167 - 6 Feb 2025
Viewed by 1191
Abstract
The worm Enchytraeus buchholzi is a new pest injuring American ginseng Panax quinquefolium. To explore its reproductive potential and then estimate its population dynamics, the authors conducted two related experiments: (1) measuring individual fecundity in its lifetime by rearing each of the [...] Read more.
The worm Enchytraeus buchholzi is a new pest injuring American ginseng Panax quinquefolium. To explore its reproductive potential and then estimate its population dynamics, the authors conducted two related experiments: (1) measuring individual fecundity in its lifetime by rearing each of the parent adults alone in a wet sandy dish at 18 and 21 °C indoors; (2) testing population growth by rearing each of the parent adults together with its offspring for a time longer than two generations at 21 °C. In Experiment I, five dependent variables, namely daily mean cocoons (DMC), cumulative cocoons (CC), eggs per cocoon (EPC), daily mean eggs (DME) and cumulative eggs (CE), were extracted, with each of them subject to a stepwise regression analysis on rearing time (T) and its power series as independent variables. Equaling to the net reproductive rate (R0), the generational adult equivalent (GAE) was calculated via a conversion of F1 generational eggs into adult equivalents (AE). In Experiment II, both an exponential and a logistic function were applied to construct regression equations. The results indicated that (1) a parent adult of E. buchholzi was able to live for a period as long as 10 and 13 full generations at the two temperatures tested and lay 84.8 and 110.6 cocoons containing 545 and 714 eggs, respectively; (2) DMC reached its maximum between 7 and 9 days of rearing and then declined slowly along a straight regression line; (3) CC rose steadily along a quadratic curve; (4) both EPC and DME varied following a cubic curve; (5) CE increased steadily along a cubic curve; (6) the new polynomial models suitably reflected the numerical growth trends of cocoons and eggs in the F1 generation in a broad sense, while corresponding derivative equations quantified both the daily reproductive potential and resistance of the worm, thus revealed its daily reproductive capacity; (7) R0 was 41.2 AE at 21 °C and 42.5 AE at 18 °C when a population of E. buchholzi lived in a niche with unlimited ambient resources; (8) this kind of temporal population generated by individual reproduction had fully demonstrated its significant, generational reproductive potential; and (9), through living in such a limited area as the wet sandy dish, bypassing an exponential growth process, the laboratory population grew up along a logistic curve from the F1 to F3 generations. The statistical relationships help to comprehend the individual reproduction of E. buchholzi, understand deeply the logical sequence and the difference between individual and population reproductions, predict population dynamics of the worm, and provide its integrated pest management with a solid basis. The experimental study has expanded theories on bionomics and population ecology, opening up a new area for research work in related fields. Full article
(This article belongs to the Section Developmental and Reproductive Biology)
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31 pages, 5936 KiB  
Review
Comparative Phytochemistry of Polyacetylenes of the Genus Artemisia (Asteraceae): Compounds with High Biological Activities and Chemotaxonomic Significance
by Harald Greger
Molecules 2025, 30(3), 537; https://doi.org/10.3390/molecules30030537 - 24 Jan 2025
Cited by 2 | Viewed by 1611
Abstract
In spite of the many chemical reports on polyacetylenes of the genus Artemisia, combined conclusions regarding their distribution and biological functions are widely missing. The aim of the present review was to arrange the diversity of polyacetylenes in the genus following biogenetic [...] Read more.
In spite of the many chemical reports on polyacetylenes of the genus Artemisia, combined conclusions regarding their distribution and biological functions are widely missing. The aim of the present review was to arrange the diversity of polyacetylenes in the genus following biogenetic aspects and group them together into characteristic structural types. The co-occurrence of the dehydrofalcarinol type with the aromatic capillen-isocoumarin type represents a characteristic biogenetic trend, clearly segregating species of the subgenus Dracunculus from those of the subgenera Artemisia and Absinthium, distinguished by the spiroketal enol ether and/or linear triyne type. Various accumulation trends toward specific structures additionally contribute to a more natural species grouping within the subgenera. Biological activities were reported for all four structural types, ranging from antifungal, insecticidal, nematicidal, and cytotoxic properties to allelopathic effects. Of particular interest were their remarkable cytotoxic potencies, from which the very high values of dehydrofalcarin-3,8-diol may be associated with the pronounced affinity of this type to form extremely stable bonds to proteins acting in signaling pathways. The aromatic acetylene capillin inhibited the viability of various tumor cells in a dose- and time-dependent manner. Its potent apoptosis-inducing activity was induced via the mitochondrial pathway. A group of spiroketal enol ethers was identified as inhibitors of PMA-induced superoxide generation. Among them, the epoxide of the isovalerate ester exhibited the highest potency. The ecological impact of acetylene formation was made apparent by the allelopathic effects of DME of the linear triyne type, and the aromatic capillen by inhibiting seed germination and growth of widespread weeds. Full article
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21 pages, 11025 KiB  
Article
Predictors of Peripheral Retinal Non-Perfusion in Clinically Significant Diabetic Macular Edema
by Martin Hein, Andrew Mehnert, Fiona Josephine, Arman Athwal, Dao-Yi Yu and Chandrakumar Balaratnasingam
J. Clin. Med. 2025, 14(1), 52; https://doi.org/10.3390/jcm14010052 - 26 Dec 2024
Viewed by 1057
Abstract
Background/Objectives: Diabetic macular edema (DME) is a significant cause of vision loss. The development of peripheral non-perfusion (PNP) might be associated with the natural course, severity, and treatment of DME. The present study seeks to understand the predictive power of central macular changes [...] Read more.
Background/Objectives: Diabetic macular edema (DME) is a significant cause of vision loss. The development of peripheral non-perfusion (PNP) might be associated with the natural course, severity, and treatment of DME. The present study seeks to understand the predictive power of central macular changes and clinico-demographic features for PNP in patients with clinically significant DME. Methods: A prospective study using contemporaneous multi-modal retinal imaging was performed. In total, 48 eyes with DME from 33 patients were enrolled. Demographic, clinical history, laboratory measures, ultrawide field photography, fluorescein angiography, optical coherence tomography (OCT), and OCT angiography results were acquired. Anatomic and vascular features of the central macula and peripheral retina were quantified from retinal images. Separate (generalized) linear mixed models were used to assess differences between PNP present and absent groups. Mixed effects logistic regression was used to assess which features have predictive power for PNP. Results: Variables with significant differences between eyes with and without PNP were insulin use (p = 0.0001), PRP treatment (p = 0.0003), and diffuse fluorescein leakage (p = 0.013). Importantly, there were no significant differences for any of the macular vascular metrics including vessel density (p = 0.15) and foveal avascular zone (FAZ) area (p = 0.58 and capillary tortuosity (p = 0.55). Features with significant predictive power (all p < 0.001) were subretinal fluid, FAZ eccentricity, ellipsoid zone disruption, past anti-VEGF therapy, insulin use, and no ischemic heart disease. Conclusions: In the setting of DME, macular vascular changes did not predict the presence of PNP. Therefore, in order to detect peripheral non-perfusion in DME, our results implicate the importance of peripheral retinal vascular imaging. Full article
(This article belongs to the Special Issue Diabetic Retinopathy: Current Concepts and Future Directions)
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19 pages, 48904 KiB  
Article
OCTNet: A Modified Multi-Scale Attention Feature Fusion Network with InceptionV3 for Retinal OCT Image Classification
by Irshad Khalil, Asif Mehmood, Hyunchul Kim and Jungsuk Kim
Mathematics 2024, 12(19), 3003; https://doi.org/10.3390/math12193003 - 26 Sep 2024
Cited by 8 | Viewed by 2034
Abstract
Classification and identification of eye diseases using Optical Coherence Tomography (OCT) has been a challenging task and a trending research area in recent years. Accurate classification and detection of different diseases are crucial for effective care management and improving vision outcomes. Current detection [...] Read more.
Classification and identification of eye diseases using Optical Coherence Tomography (OCT) has been a challenging task and a trending research area in recent years. Accurate classification and detection of different diseases are crucial for effective care management and improving vision outcomes. Current detection methods fall into two main categories: traditional methods and deep learning-based approaches. Traditional approaches rely on machine learning for feature extraction, while deep learning methods utilize data-driven classification model training. In recent years, Deep Learning (DL) and Machine Learning (ML) algorithms have become essential tools, particularly in medical image classification, and are widely used to classify and identify various diseases. However, due to the high spatial similarities in OCT images, accurate classification remains a challenging task. In this paper, we introduce a novel model called “OCTNet” that integrates a deep learning model combining InceptionV3 with a modified multi-scale attention-based spatial attention block to enhance model performance. OCTNet employs an InceptionV3 backbone with a fusion of dual attention modules to construct the proposed architecture. The InceptionV3 model generates rich features from images, capturing both local and global aspects, which are then enhanced by utilizing the modified multi-scale spatial attention block, resulting in a significantly improved feature map. To evaluate the model’s performance, we utilized two state-of-the-art (SOTA) datasets that include images of normal cases, Choroidal Neovascularization (CNV), Drusen, and Diabetic Macular Edema (DME). Through experimentation and simulation, the proposed OCTNet improves the classification accuracy of the InceptionV3 model by 1.3%, yielding higher accuracy than other SOTA models. We also performed an ablation study to demonstrate the effectiveness of the proposed method. The model achieved an overall average accuracy of 99.50% and 99.65% with two different OCT datasets. Full article
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13 pages, 2357 KiB  
Review
Efficacy and Safety of Fluocinolone Acetonide Implant in Diabetic Macular Edema: Practical Guidelines from Reference Center
by Lucas Sejournet, Thibaud Mathis, Victor Vermot-Desroches, Rita Serra, Ines Fenniri, Philippe Denis and Laurent Kodjikian
Pharmaceutics 2024, 16(9), 1183; https://doi.org/10.3390/pharmaceutics16091183 - 7 Sep 2024
Cited by 3 | Viewed by 1427
Abstract
Diabetic macular edema (DME) is a common complication of diabetic retinopathy. Treatment with intravitreal injections is effective in most cases but is associated with a high therapeutic burden for patients. This implies the need for long-term treatments, such as the fluocinolone acetonide (FAc) [...] Read more.
Diabetic macular edema (DME) is a common complication of diabetic retinopathy. Treatment with intravitreal injections is effective in most cases but is associated with a high therapeutic burden for patients. This implies the need for long-term treatments, such as the fluocinolone acetonide (FAc) implant. A review of basic science, pharmacology, and clinical data was conducted to provide a state-of-the-art view of the FAc implant in 2024. Although generally well tolerated, the FAc implant has been associated with ocular hypertension and cataract, and caution should be advised to the patients in this regard. By synthesizing information across these domains, a comprehensive evaluation can be attained, facilitating informed decision-making regarding the use of the FAc implant in the management of DME. The main objective of this review is to provide clinicians with guidelines on how to introduce and use the FAc implant in a patient with DME. Full article
(This article belongs to the Special Issue Drugs and Drug Delivery for Diabetes Mellitus Treatment, 2nd Edition)
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43 pages, 1756 KiB  
Review
E-Fuels: A Comprehensive Review of the Most Promising Technological Alternatives towards an Energy Transition
by Sonia Dell’Aversano, Carlo Villante, Katia Gallucci, Giuseppina Vanga and Andrea Di Giuliano
Energies 2024, 17(16), 3995; https://doi.org/10.3390/en17163995 - 12 Aug 2024
Cited by 29 | Viewed by 13675
Abstract
E-fuels represent a crucial technology for transitioning to fossil-free energy systems, driven by the need to eliminate dependence on fossil fuels, which are major environmental pollutants. This study investigates the production of carbon-neutral synthetic fuels, focusing on e-hydrogen (e-H2) generated from [...] Read more.
E-fuels represent a crucial technology for transitioning to fossil-free energy systems, driven by the need to eliminate dependence on fossil fuels, which are major environmental pollutants. This study investigates the production of carbon-neutral synthetic fuels, focusing on e-hydrogen (e-H2) generated from water electrolysis using renewable electricity and carbon dioxide (CO2) captured from industrial sites or the air (CCUS, DAC). E-H2 can be converted into various e-fuels (e-methane, e-methanol, e-DME/OME, e-diesel/kerosene/gasoline) or combined with nitrogen to produce e-ammonia. These e-fuels serve as efficient energy carriers that can be stored, transported, and utilized across different energy sectors, including transportation and industry. The first objective is to establish a clear framework encompassing the required feedstocks and production technologies, such as water electrolysis, carbon capture, and nitrogen production techniques, followed by an analysis of e-fuel synthesis technologies. The second objective is to evaluate these technologies’ technological maturity and sustainability, comparing energy conversion efficiency and greenhouse gas emissions with their electric counterparts. The sustainability of e-fuels hinges on using renewable electricity. Challenges and future prospects of an energy system based on e-fuels are discussed, aiming to inform the debate on e-fuels’ role in reducing fossil fuel dependency. Full article
(This article belongs to the Section B: Energy and Environment)
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14 pages, 2392 KiB  
Article
The Association of Delayed Milk Ejection with Milking Performance in Holstein Cows in a Large Dairy Herd with Suboptimal Premilking Teat Stimulation
by Ajay Singh, Madeleine Eve Spellman, Haritha Somula, Mohammad Osamah Dahl and Matthias Wieland
Animals 2024, 14(12), 1828; https://doi.org/10.3390/ani14121828 - 20 Jun 2024
Cited by 1 | Viewed by 1370
Abstract
The primary objective was to investigate the association between delayed milk ejection (DME) and the average milk flow rate, milking unit-on time, and duration in a low milk flow rate in Holstein dairy cows in a large dairy herd with suboptimal premilking teat [...] Read more.
The primary objective was to investigate the association between delayed milk ejection (DME) and the average milk flow rate, milking unit-on time, and duration in a low milk flow rate in Holstein dairy cows in a large dairy herd with suboptimal premilking teat stimulation. Our second objective was to study the association between peak lactation milk yield and the occurrence of DME. This longitudinal field study was conducted at a 4300-cow dairy farm with a thrice-daily milking schedule over a 1-week period. We analyzed data from 61,677 cow milking observations from 2937 cows. Delayed milk ejection was defined as present if the 30–60 s milk flow rate was ≤3.1 kg/min. The mean average milk flow rate (MAMF, kg/min), mean milking unit-on time (MMUT, s), and mean duration of a low milk flow rate (MLMF, s) were calculated as the mean values from the 21 milking observations. General linear multivariable models revealed associations of DME with MAMF, MMUT, and MLMF. A multivariable ordinal logistic regression model revealed an association between peak lactation milk yield and DME. Cows with lower peak lactation milk yield had greater odds of exhibiting a higher frequency level of DME. The observed associations between DME and milking performance indices suggest that DME can negatively affect milking and parlor efficiency. Peak lactation milk yield may serve as a proxy to estimate cows’ risk of recurrent DME. Future research is warranted to test if alleviating DME through, for example, a modified milking routine influences the milking performance indices described herein. Full article
(This article belongs to the Section Cattle)
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16 pages, 3655 KiB  
Article
Observation of Agonistic Behavior in Pacific White Shrimp (Litopenaeus vannamei) and Transcriptome Analysis
by Bo Wu, Chenxi Zhao, Xiafei Zheng, Zhilan Peng and Minhai Liu
Animals 2024, 14(11), 1691; https://doi.org/10.3390/ani14111691 - 5 Jun 2024
Cited by 3 | Viewed by 2217
Abstract
Agonistic behavior has been identified as a limiting factor in the development of intensive L. vannamei aquaculture. However, the characteristics and molecular mechanisms underlying agonistic behavior in L. vannamei remain unclear. In this study, we quantified agonistic behavior through a behavioral observation system [...] Read more.
Agonistic behavior has been identified as a limiting factor in the development of intensive L. vannamei aquaculture. However, the characteristics and molecular mechanisms underlying agonistic behavior in L. vannamei remain unclear. In this study, we quantified agonistic behavior through a behavioral observation system and generated a comprehensive database of eyestalk and brain ganglion tissues obtained from both aggressive and nonaggressive L. vannamei employing transcriptome analysis. The results showed that there were nine behavior patterns in L. vannamei which were correlated, and the fighting followed a specific process. Transcriptome analysis revealed 5083 differentially expressed genes (DEGs) in eyestalk and 1239 DEGs in brain ganglion between aggressive and nonaggressive L. vannamei. Moreover, these DEGs were primarily enriched in the pathways related to the energy metabolism process and signal transduction. Specifically, the phototransduction (dme04745) signaling pathway emerges as a potential key pathway for the adjustment of the L. vannamei agonistic behavior. The G protein-coupled receptor kinase 1-like (LOC113809193) was screened out as a significant candidate gene within the phototransduction pathway. Therefore, these findings contribute to an enhanced comprehension of crustacean agonistic behavior and provide a theoretical basis for the selection and breeding of L. vannamei varieties suitable for high-density aquaculture environments. Full article
(This article belongs to the Collection Behavioral Ecology of Aquatic Animals)
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